CiteULike: Tag filter

Estimation of orientation tensors for simple signals by means of second-order filters

Klas Nordberg — 2005-11-12T22:34:08-00:00

Signal Processing: Image Communication, Vol. 20, No. 6. (July 2005), pp. 582-594.

Tensors have become a popular tool for representation of local orientation and can be used also for estimation of velocity. A number of computational approaches have been presented for tensor estimation which, however, are difficult to analyze or compare since there has been no common framework in which analysis or comparisons can be made. In this article, we propose such a framework based on second-order filters and show how it applies to three different methods for tensor estimation. The framework contains a few conditions on the filters which are sufficient to obtain correctly oriented rank one tensors for the case of simple signals. It also allows the derivation of explicit expressions for the variation of the tensor across oriented structures which, e.g., can be used to formulate conditions for phase invariance.

Parameter sensitivity of three Kalman filter schemes for assimilation of water levels in shelf sea models

JVT S[x00f8]rensen — 2006-11-27T13:21:16-00:00

Ocean Modelling, Vol. 11, No. 3-4. (2006), pp. 441-463.

In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter. A sensitivity analysis of key parameters in the schemes is undertaken for a setup in an idealised bay. The sensitivity of the resulting root mean square error (RMSE) is shown to be low to moderate. Hence the schemes are robust within an acceptable range and their application even with misspecified parameters is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact of assimilating even very few measurements.

The bilinear Z transform by Pascal matrix and its application in the design of digital filters

B Psenicka — 2007-10-13T08:58:12-00:00

Signal Processing Letters, IEEE, Vol. 9, No. 11. (2002), pp. 368-370.

In this letter, the Pascal matrix is used for transforming the normalized analog transfer function H(s) from the lowpass to the lowpass and highpass discrete transfer functions H(z). This algorithm is very simple; therefore, the transfer function H(s) can be easily transformed to the z domain using an appropriate calculator. The inverse Pascal matrix can be obtained without computing the determinant of the system, and then it is very easy to obtain the associated analog transfer function H(s) if the discrete transfer function H(z) is known.

On the Learning Mechanism of Adaptive Filters

Vítor Nascimento — 2007-06-14T13:23:11-00:00

This paper highlights, both analytically and by simulations, some interesting phenomena regarding the behavior of ensemble-average learning curves of adaptive filters that may have gone unnoticed. Among other results, the paper shows that even ensemble-average learning curves of single-tap LMS filters actually exhibit two distinct rates of convergence; one for the initial time instants and another, faster, for later time instants. Also, such curves tend to converge faster than predicted by...

An MCMC-based Particle Filter

For Multiple — 2005-10-10T19:21:26-00:00

We describe a Markov chain Monte Carlo based particle filter that e#ectively deals with interacting targets, i.e., targets that are influenced by the proximity and/or behavior of other targets. Such interactions cause problems for traditional approaches to the data association problem. In response, we developed a joint tracker that includes a more sophisticated motion model to maintain the identity of targets throughout an interaction, drastically reducing tracker failures. The paper...

The Unscented Particle Filter

Rudolph van der Merwe — 2005-10-10T19:23:13-00:00

(Nov 2001)

In this paper, we propose a new particle filter based on sequential importance sampling. The algorithm uses a bank of unscented filters to obtain the importance proposal distribution. This proposal has two very "nice" properties. Firstly, it makes efficient use of the latest available information and, secondly, it can have heavy tails. As a result, we find that the algorithm outperforms standard particle filtering and other nonlinear filtering methods very substantially. This experimental...

Unscented filtering and nonlinear estimation

SJ Julier — 2006-05-09T10:39:00-00:00

Proceedings of the IEEE, Vol. 92, No. 3. (2004), pp. 401-422.

The extended Kalman filter (EKF) is probably the most widely used estimation algorithm for nonlinear systems. However, more than 35 years of experience in the estimation community has shown that is difficult to implement, difficult to tune, and only reliable for systems that are almost linear on the time scale of the updates. Many of these difficulties arise from its use of linearization. To overcome this limitation, the unscented transformation (UT) was developed as a method to propagate mean and covariance information through nonlinear transformations. It is more accurate, easier to implement, and uses the same order of calculations as linearization. This paper reviews the motivation, development, use, and implications of the UT.

Statistical en-route filtering of injected false data in sensor networks

Fan Ye — 2006-02-28T05:02:19-00:00

INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, Vol. 4 (2004), pp. 2446-2457 vol.4.

In a large-scale sensor network individual sensors are subject to security compromises. A compromised node can inject into the network large quantities of bogus sensing reports which, if undetected, would be forwarded to the data collection point (i.e. the sink). Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. We present a statistical en-route filtering (SEF) mechanism that can detect and drop such false reports. SEF requires that each sensing report be validated by multiple keyed message authentication codes (MACs), each generated by a node that detects the same event. As the report is forwarded, each node along the way verifies the correctness of the MACs probabilistically and drops those with invalid MACs at earliest points. The sink further filters out remaining false reports that escape the en-route filtering. SEF exploits the network scale to determine the truthfulness of each report through collective decision-making by multiple detecting nodes and collective false-report-detection by multiple forwarding nodes. Our analysis and simulations show that, with an overhead of 14 bytes per report, SEF is able to drop 80/spl sim/90% injected false reports by a compromised node within 10 forwarding hops, and reduce energy consumption by 50% or more in many cases.

Optimal ramp edge detection using expansion matching

Zhiqian Wang — 2007-11-16T15:16:06-00:00

Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 11. (1996), pp. 1092-1097.

In practical images, ideal step edges are actually transformed into ramp edges, due to the general low pass filtering nature of imaging systems. This paper discusses the application of the expansion matching (EXM) method for optimal ramp edge detection. EXM optimizes a novel matching criterion called discriminative signal-to-noise ratio (DSNR) and has been shown to robustly recognize templates under conditions of noise, severe occlusion, and superposition. We show that our ramp edge detector performs better than the ramp detector obtained from Canny's criteria in terms of DSNR and is relatively easier to derive for various noise levels and slopes

Kalman Filter-based Algorithms for Estimating Depth from Image Sequences

Larry Matthies — 2008-01-18T08:52:39-00:00

International Journal of Computer Vision, Vol. 3, No. 3. (1989), pp. 209-238.

Using known camera motion to estimate depth from image sequences is an important problem in robot vision. Many applications of depth-from-motion, including navigation and manipulation, require algorithms that can estimate depth in an on-line, incremental fashion. This requires a representation that records the uncertainty in depth estimates and a mechanism that integrates new measurements with existing depth estimates to reduce the uncertainty over time. Kalman filtering provides this...

Maximum A Posteriori Speckle Filtering And First Order Texture Models In Sar Images

A Lopes — 2005-11-11T15:45:33-00:00

Geoscience and Remote Sensing Symposium, 1990. IGARSS '90. 'Remote Sensing Science for the Nineties'., 10th Annual International (1990), pp. 2409-2412.

Steerable wedge filters for local orientation analysis

EP Simoncelli — 2005-09-30T07:43:55-00:00

Image Processing, IEEE Transactions on, Vol. 5, No. 9. (1996), pp. 1377-1382.

Steerable filters have been used to analyze local orientation patterns in imagery. Such filters are typically based on directional derivatives, whose symmetry produces orientation responses that are periodic with period π, independent of image structure. We present a more general set of steerable filters that alleviate this problem

Adaptive restoration of images with speckle

D Kuan — 2005-11-08T10:46:43-00:00

Acoustics, Speech, and Signal Processing [see also IEEE Transactions on Signal Processing], IEEE Transactions on, Vol. 35, No. 3. (1987), pp. 373-383.

Speckle is a granular noise that inherently exists in all types of coherent imaging systems. The presence of speckle in an image reduces the resolution of the image and the detectability of the target. Many speckle reduction algorithms assume speckle noise is multiplicative. We instead model the speckle according to the exact physical process of coherent image formation. Thus, the model includes signal-dependent effects and accurately represents the higher order statistical properties of speckle that are important to the restoration procedure. Various adaptive restoration filters for intensity speckle images are derived based on different model assumptions and a nonstationary image model. These filters respond adaptively to the signal-dependent speckle noise and the nonstationary statistics of the original image.

A review of speckle filtering in the context of estimation theory

R Touzi — 2005-11-11T18:20:59-00:00

Geoscience and Remote Sensing, IEEE Transactions on, Vol. 40, No. 11. (2002), pp. 2392-2404.

Speckle filter performance depends strongly on the speckle and scene models used as the basis for filter development. These models implicitly incorporate certain assumptions about speckle, scene, and observed signals. In this study, the multiplicative and the product speckle models, which have been used for the development of most of the well-known filters, are analyzed, and their implicit assumptions with regard to the stationarity-nonstationarity nature of speckle are discussed. This leads to the definition of two categories of speckle filters: the stationary and the nonstationary multiplicative speckle model filters. The various approximate models used for the multiplicative speckle noise model are assessed as functions of speckle and scene characteristics to derive the requirements on scene signal variations for the validity of both the stationary and nonstationary multiplicative speckle models. Speckle filtering is then studied in the context of estimation theory, so as to develop a procedure for speckle filtering. It is shown that speckle filtering can be effective only in locally stationary scenes. Regions in which the signals are not stationary have to be filtered separately using a priori scene templates for the best matching of nonstationary scene features. The use of multiresolution techniques is crucial for accurate estimation of filter parameters. Under the guidance of the speckle filtering procedure, structural-multiresolution versions of the Lee (1980) and Frost et al. (1982) filters are developed for optimum application of these filters in the context of nonstationary scene signals.

Tracking Deforming Objects Using Particle Filtering for Geometric Active Contours

Yogesh Rathi — 2007-11-14T15:02:35-00:00

Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, No. 8. (2007), pp. 1470-1475.

Tracking deforming objects involves estimating the global motion of the object and its local deformations as a function of time. Tracking algorithms using Kalman filters or particle filters have been proposed for finite dimensional representations of shape, but these are dependent on the chosen parametrization and cannot handle changes in curve topology. Geometric active contours provide a framework which is parametrization independent and allow for changes in topology. In the present work, we formulate a particle filtering algorithm in the geometric active contour framework that can be used for tracking moving and deforming objects. To the best of our knowledge, this is the first attempt to implement an approximate particle filtering algorithm for tracking on a (theoretically) infinite dimensional state space.

Adaptive speckle filters and scene heterogeneity

A Lopes — 2005-11-11T18:18:57-00:00

Geoscience and Remote Sensing, IEEE Transactions on, Vol. 28, No. 6. (1990), pp. 992-1000.

The presence of speckle in radar images makes the radiometric and textural aspects less efficient for class discrimination. Many adaptive filters have been developed for speckle reduction, the most well known of which are analyzed. It is shown that they are based on a test related to the local coefficient of variation of the observed image, which describes the scene heterogeneity. Some practical criteria are introduced to modify the filters in order to make them more efficient. The filters are tested on a simulated synthetic aperture radar (SAR) image and an SAR-580 image. As was expected, the new filters perform better, i.e. they average the homogeneous areas better and preserve texture information, edges, linear features, and point target responses better at the same time. Moreover, they can be adapted to features other than the coefficient of variation to reduce the speckle while preserving the corresponding information

A refined gamma MAP SAR speckle filter with improved geometrical adaptivity

A Baraldi — 2005-11-11T18:03:42-00:00

Geoscience and Remote Sensing, IEEE Transactions on, Vol. 33, No. 5. (1995), pp. 1245-1257.

A modified version of the refined gamma maximum-a-posteriori (RGMAP) speckle filter, which is found in the literature, is presented. The traditional RGMAP speckle filter first defects contours belonging to step edges and thin linear structures, then applies the RGMAP filter to local statistics extracted from rectangular masks that do not cross image contours. The proposed modified RGMAP (MRGMAP) filter first exploits local operators belonging to the odd-symmetric filter category employed by RGMAP to detect image segments, then it computes local statistics over areas that are not necessarily rectangular, but are subsets of the image segments having any possible shape. Therefore, MRGMAP enhances the RGMAP ability in exploiting shape adaptive windowing near image contours, where speckle is not fully developed. The MRGMAP computation time is estimated to be of the same magnitude of that of the original RGMAP, the latter depending on the number of filter categories being employed. The qualitative and quantitative results of the MRGMAP filter applied to real SAR images are satisfactory as the filter seems to be effective in speckle removal whereas it retains edge sharpness and subtle details. However, tests on simulated SAR images must still be performed in order to provide definitive evidence supporting MRGMAP effectiveness. Since MRGMAP typically removes image structures featuring a constant reflectivity gradient, this filter is not particularly suitable for image enhancement in human photo-interpretation. MRGMAP can be rather employed as a preprocessing module in a computer-based SAR image classification procedure based on segment mean value analysis

Microfluidic arrays for logarithmically perfused embryonic stem cell culture.

L Kim — 2007-09-17T13:29:22-00:00

Lab Chip, Vol. 6, No. 3. (March 2006), pp. 394-406.

We present a microfluidic device for culturing adherent cells over a logarithmic range of flow rates. The device sets flow rates through four separate cell-culture chambers using syringe-driven flow and a network of fluidic resistances. The design is easy to fabricate with no on-chip valves and is scalable both in the number of culture chambers as well as in the range of applied flow rates. Using particle velocimetry, we have characterized the flow-rate range. We have also demonstrated an extension of the design that combines the logarithmic flow-rate functionality with a logarithmic concentration gradient across the array. Using fluorescence measurements we have verified that a logarithmic concentration gradient was established in the extended device. Compared with static cell culture, both devices enable greater control over the soluble microenvironment by controlling the transport of molecules to and away from the cells. This approach is particularly relevant for cell types such as embryonic stem cells (ESCs) which are especially sensitive to the microenvironment. We have demonstrated for the first time culture of murine ESCs (mESCs) in continuous, logarithmically scaled perfusion for 4 days, with flow rates varying >300x across the array. Cells grown in the slowest flow rate did not proliferate, while colonies grown in higher flow rates exhibited healthy round morphology. We have also demonstrated logarithmically scaled continuous perfusion culture of 3T3 fibroblasts for 3 days, with proliferation at all flow rates except the slowest rate.

Consumer-food systems: why type I functional responses are exclusive to filter feeders

Jonathan Jeschke — 2008-03-27T12:13:50-00:00

Biological Reviews, Vol. 79, No. 2. (2004), pp. 337-349.

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An introduction to matched filters

G Turin — 2007-09-25T05:45:39-00:00

Information Theory, IEEE Transactions on, Vol. 6, No. 3. (1960), pp. 311-329.

In a tutorial exposition, the following topics are discussed: definition of a matched filter; where matched filters arise; properties of matched filters; matched-filter synthesis and signal specification; some forms of matched filters.

Optical delay lines based on optical filters

G Lenz — 2006-11-21T05:01:24-00:00

Quantum Electronics, IEEE Journal of, Vol. 37, No. 4. (2001), pp. 525-532.

Optical delay lines have some important applications, notably in optical communication systems and in phased arrays. These devices are based on the concept of optical group delay, which, in turn, can be understood as the property of an optical filter. Optical filters are well-understood devices and, in particular, their dispersive properties determine the group delay response. We review these dispersive properties and point out some of the inherent tradeoffs involved in generating large group delay. Fiber Bragg gratings and recent results on optical all-pass filters are used as examples

Fast bilateral filtering for the display of high-dynamic-range images

Fr&\#233;do Durand — 2006-08-08T01:29:53-00:00

(2002), pp. 257-266.

Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification

Jonathan Zdziarski — 2006-09-22T16:18:54-00:00

(01 July 2005)

Join author John Zdziarski for a look inside the brilliant minds that have conceived clever new ways to fight spam in all its nefarious forms. This landmark title describes, in-depth, how statistical filtering is being used by next-generation spam filters to identify and filter unwanted messages, how spam filtering works and how language classification and machine learning combine to produce remarkably accurate spam filters. After reading Ending Spam, you'll have a complete understanding of the mathematical approaches used by today's spam filters as well as decoding, tokenization, various algorithms (including Bayesian analysis and Markovian discrimination) and the benefits of using open-source solutions to end spam. Zdziarski interviewed creators of many of the best spam filters and has included their insights in this revealing examination of the anti-spam crusade. If you're a programmer designing a new spam filter, a network admin implementing a spam-filtering solution, or just someone who's curious about how spam filters work and the tactics spammers use to evade them, Ending Spam will serve as an informative analysis of the war against spammers. TOC Introduction PART I: An Introduction to Spam Filtering Chapter 1: The History of Spam Chapter 2: Historical Approaches to Fighting Spam Chapter 3: Language Classification Concepts Chapter 4: Statistical Filtering Fundamentals PART II: Fundamentals of Statistical Filtering Chapter 5: Decoding: Uncombobulating Messages Chapter 6: Tokenization: The Building Blocks of Spam Chapter 7: The Low-Down Dirty Tricks of Spammers Chapter 8: Data Storage for a Zillion Records Chapter 9: Scaling in Large Environments PART III: Advanced Concepts of Statistical Filtering Chapter 10: Testing Theory Chapter 11: Concept Identification: Advanced Tokenization Chapter 12: Fifth-Order Markovian Discrimination Chapter 13: Intelligent Feature Set Reduction Chapter 14: Collaborative Algorithms Appendix: Shining Examples of Filtering Index

Direct Kalman filtering approach for GPS/INS integration

Honghui Qi — 2007-05-21T23:00:11-00:00

Aerospace and Electronic Systems, IEEE Transactions on, Vol. 38, No. 2. (2002), pp. 687-693.

We present a novel Kalman filtering approach for GPS/INS integration. In the approach, GPS and INS nonlinearities are preprocessed prior to a Kalman filter. The GPS preprocessed data are taken as measurement input, while the INS preprocessed data are taken as additional information for the state prediction of the Kalman filter. The advantage of this approach, over the well-studied (extended) Kalman filtering approaches is that a simple and linear Kalman filter can be implemented to achieve significant computation saving with very competitive performance figures

Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems

Cosma Shalizi — 2007-01-06T15:43:25-00:00

(29 Jul 2005)

Most current methods for identifying coherent structures in spatially-extended systems rely on prior information about the form which those structures take. Here we present two new approaches to automatically filter the changing configurations of spatial dynamical systems and extract coherent structures. One, local sensitivity filtering, is a modification of the local Lyapunov exponent approach suitable to cellular automata and other discrete spatial systems. The other, local statistical complexity filtering, calculates the amount of information needed for optimal prediction of the system's behavior in the vicinity of a given point. By examining the changing spatiotemporal distributions of these quantities, we can find the coherent structures in a variety of pattern-forming cellular automata, without needing to guess or postulate the form of that structure. We apply both filters to elementary and cyclical cellular automata (ECA and CCA) and find that they readily identify particles, domains and other more complicated structures. We compare the results from ECA with earlier ones based upon the theory of formal languages, and the results from CCA with a more traditional approach based on an order parameter and free energy. While sensitivity and statistical complexity are equally adept at uncovering structure, they are based on different system properties (dynamical and probabilistic, respectively), and provide complementary information.

Simultaneous Feature Selection and Clustering Using Mixture Models

Martin Law — 2006-07-13T11:54:18-00:00

Clustering is a common unsupervised learning technique used to discover group structure in a set of data. While there exist many algorithms for clustering, the important issue of feature selection, that is, what attributes of the data should be used by the clustering algorithms, is rarely touched upon. Feature selection for clustering is di#cult because, unlike in supervised learning, there are no class labels for the data and so no obvious criteria to guide the search. Another important...

Analysis of the time-frequency representation using the Gamma filter

S Celebi — 2007-05-17T18:59:42-00:00

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on, Vol. 5 (1996), pp. 2587-2590 vol. 5.

We analyze the performance of the time-frequency representation method that utilizes the Gamma filter. Gamma filter which can be implemented as a cascade of identical first order lowpass filters generates at its taps the Poisson moments of the input signal. These moments carry spectral information about the recent history of the input signal. Due to the inherent time window embedded in the Gamma filter, the moments are local both in time and frequency. Hence, they can be used to construct a time-frequency representation as an alternative to the conventional methods of short term Fourier transform (STFT), cepstrum, etc. The appeal of the proposed method comes from the fact that in the analog domain the moments are readily available as a continuous time electrical signal and can be physically measured, rather than computed offline by a digital computer. Furthermore, for a faithful representation, it is sufficient to observe the moments at the information rate (nonstationarity rate) rather than the usually higher Nyquist rate. The observed moments can be fed into an artificial neural network (ANN) for tasks like prediction, classification and identification. This work studies the performance of the proposed representation scheme as a function of the system parameters, such as; time scale, number of moments and number of bands on the estimation quality

Adaline with adaptive recursive memory

B De Vries — 2007-10-25T18:03:22-00:00

Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop (1991), pp. 101-110.

The authors present a generalization of Widrow's adaptive linear combiner with an adaptive recursive memory. Expressions for memory depth and resolution are derived. The LMS procedure is extended to adapt the memory depth and resolution so as to match the signal characteristics. The particular memory structure, gamma memory, was originally developed as part of a neural net model for temporal processing

Time-variant CIC-filters for sample-rate conversion with arbitrary rational factors

M Henker — 2006-10-24T09:07:33-00:00

(1999)

Sample rate conversion (SRC) with rational factors can be realized by interpolation followed by decimation, where CIC-Filters [1] can be chosen for either. However, the necessary increase of the sample rate that goes with the interpolation is not feasible in most RF-applications. Therefore a time-variant implementation of CIC-filters is presented which circumvents the high intermediate sample rate. This time-variant implementation results in a linear periodically time-variant system (LPTV)...

Sample Rate Conversion in Software Radio Terminals

T Hentschel — 2006-10-24T09:06:39-00:00

Feasibility of Software Radio mainly depends on the availability of a suitable hardware platform. A basic feature of this hardware platform is the ability to process signals of different mobile communications standards, which are usually based upon a diversity of master clock rates. Hence, the conversion between different sample rates is an important functionality of a Software Radio receiver. Preferably realized digitally, sample-rate conversion is conventionally regarded as interpolation. ...

Reduced Complexity Comb-Filters for Decimation and Interpolation in Mobile Communications Terminals

T Hentschel — 2006-10-24T09:01:49-00:00

(1999)

In mobile communications systems complexity and efficiency are issues of paramount importance. Therefore when implementing integer factor sample-rate conversion, comb-filters - especially cascaded-integratorcomb (CIC) filters - are a good choice of realizing linearphase filters with low complexity. However, neither the direct implementation of comb-filters as transversal filters nor their implementation as CIC-filters are minimal realizations. Since both, decimators and interpolators are...

Pipelined Hogenauer CIC filters using field-programmable logic and residue number system

A Garcia — 2006-10-24T08:59:56-00:00

(1998)

Field-Programmable Logic (FPL) is on the verge of revolutionizing digital signal processing (DSP) in the manner that programmable DSP microprocessors did nearly two decades ago. While FPL densities and performance have steadily improved to the point where some DSP solutions can be integrated into a single FPL chip, they still have limited use in high-precision high-bandwidth applications. In this paper it is shown that in such cases, the residue number system (RNS) can be an enabling...

A Comparison Design of Comb Decimators for Delta-Sigma Analog-to-Digital Converters

Yonghong Gao — 2006-10-24T12:40:56-00:00

In this paper we present a comparison design of comb decimators based on nonrecursive algorithm and recursive algorithm. Compared with the recursive algorithm, the main advantage of non-recursive algorithm is its abilities of reducing power consumption and increasing circuit speed in case of higher filter orders and decimation ratios. Based on the non-recursive algorithm, a decimator with programmable orders (3rd, 4th and 5th), decimation factors (8, 16, 32 and 64) and input bits (1 and 2 bits) ...

Efficient polyphase decomposition of comb decimation filters in $ΣΔ$ analog-to-digital converters

H Aboushady — 2006-10-24T12:32:45-00:00

(2001)

A power efficient multi-rate multi-stage Comb decimation filter for mono-bit and multi-bit A A/D converters is presented. Polyphase decomposition in all stages, with high decimation factor in the first stage, is used to significantly reduce the sampling frequency of the Comb filter. Several implementations indicate that proper choice of the first stage decimation factor can considerably improve power consumption, area and maximum sampling frequency. In multibit .A A/Ds, this optimum first stage ...

Low-power comb decimation filters using polyphase decomposition for mono-bit sigmadelta analog-to-digital converters

Y Dumonteix — 2006-10-24T12:31:18-00:00

(2000)

A power efficient multirate multistage Comb decimation filter for monobit A/D converters is presented. Polyphase decomposition in all stages with high decimation factor in the first stage, are used to reduce the frequency of the input signal. Several implementations have shown that proper choice of the decimation factor of the first stage can reduce power consumption by more than 30% The multistage architecture makes the total decimation factor easily programmable and suitabale for...

Design Of RNS Frequency Sampling Filter Banks

Uwe Bäse — 2006-10-24T12:30:25-00:00

Frequency sampling filters (FSF) are of interest to the designers of multirate filter banks due to their intrinsic loworder, complexity, and linear phase behavior. Fast FSFs residing in smaller packages will be required to support future high-bandwidth, mobile image and signal processing applications. Since FSF designs rely on the exact annihilation of selected poles-zeros, a new facilitating technology is required which is fast, compact, and numerically exact. Exact FSF pole-zero annihilation...

Shield: vulnerability-driven network filters for preventing known vulnerability exploits

Helen Wang — 2005-06-21T00:04:50-00:00

Vol. 34, No. 4. (October 2004), pp. 193-204.

Marginalized particle filters for mixed linear/nonlinear state-space models

T Schon — 2008-01-22T10:21:56-00:00

Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], Vol. 53, No. 7. (2005), pp. 2279-2289.

The particle filter offers a general numerical tool to approximate the posterior density function for the state in nonlinear and non-Gaussian filtering problems. While the particle filter is fairly easy to implement and tune, its main drawback is that it is quite computer intensive, with the computational complexity increasing quickly with the state dimension. One remedy to this problem is to marginalize out the states appearing linearly in the dynamics. The result is that one Kalman filter is associated with each particle. The main contribution in this paper is the derivation of the details for the marginalized particle filter for a general nonlinear state-space model. Several important special cases occurring in typical signal processing applications will also be discussed. The marginalized particle filter is applied to an integrated navigation system for aircraft. It is demonstrated that the complete high-dimensional system can be based on a particle filter using marginalization for all but three states. Excellent performance on real flight data is reported.

Microfiltration Membranes: Characteristics and Manufacturing

Oscar Reif — 2008-02-04T20:49:18-00:00

Sterile Filtration (2006), pp. 73-103.

Membrane filtration is used within a multitude of processes ranging from dialysis to desalination processes to sterilizing filtration in the pharmaceutical industry. Membranes, nevertheless, have to have special characteristics and properties to serve such specific applications. Microfiltration membranes are utilized in a large range of membrane polymers and structures, which all have individual production process steps to achieve consistently the same membrane parameters. This chapter discusses membrane polymers and production processes in detail.

On latency compensation and its effects on head-motion trajectories in virtual environments

Jiann-Rong Wu — 2008-05-13T14:36:52-00:00

The Visual Computer, Vol. 16, No. 2. (March 2000), pp. 79-90.

Use of a modified kalman filter for a visually coupled system application

P Dunnett — 2008-03-12T16:30:53-00:00

Virtual Reality, Vol. 1, No. 1. (29 June 1995), pp. 57-67.

Spatial tracking devices are frequently used in virtual environments, such as in the case of helmet mounted displays, to dynamically determine the user's viewpoint and line of sight. Temporal distortion effects are perceived by the user as a result of the lag between head movement and visual feedback. Measurements of phase lag have been made and to help alleviate these problems, predictive filtering techniques are frequently used. We report on studies that have been made in the use of a modified Kalman filter algorithm. The implementation provides favourable results in terms of reduction on the effect of phase lag.

A 3D tracking experiment on latency and its compensation methods in virtual environments

Jiann-Rong Wu — 2008-05-13T12:15:25-00:00

(1995), pp. 41-49.

Detail-preserving image information restoration guided by SVM based noise mapping

P Pankajakshan — 2007-05-18T10:54:26-00:00

Digital Signal Processing, Vol. 17, No. 3. (May 2007), pp. 561-577.

In this paper, we propose a new method to solve the problem of fixed-valued impulsive noise reduction in images. Nonlinear filter like the median filter (MF) is useful for reducing random noise and periodical patterns, but direct median filtering have undesirable side effects such as smoothening of noise free regions, which results in loss of image detail and distortion of the signal. Impulse noise is suppressed by selectively filtering the contaminated signal regions only, thus minimizing distortion of clean passages and loss of high frequencies. In the first phase, support vector machines (SVM) are used to segment the set of pixels N that are likely to be contaminated by the mixed impulses. In the second phase, the image is restored by employing a combination of the best neighborhood match filter (BNM) and the modified multi-shell median filter (MMMF) to these segmented regions. This method combines the effectiveness of the best neighborhood matching (BNM) filter in suppression of the noise components while adapting itself to the local image structures, and the edge and finer image detail preserving characteristics of the MMMF. To support our proposed method, numerical results are also provided, which indicate that the filter is extremely useful for preserving edges or monotonic changes in trend, while eliminating short duration impulses of high density.

Modeling of time-interleaved ADCs with nonlinear hybrid filter banks

Christian Vogel — 2008-07-14T20:19:12-00:00

AEU - International Journal of Electronics and Communications, Vol. 59, No. 5. (15 July 2005), pp. 288-296.

In this paper, we model time-interleaved analog-to-digital converters (TIADCs) with nonlinear hybrid filter banks (NHFBs), which greatly unifies and simplifies the analysis of TIADCs. The input/output relation of such a nonlinear hybrid filter bank can be used to describe combined offset, gain, aperture delay, input behavior, and nonlinearity mismatches and is therefore an extendable starting point for profound analyses of TIADC behaviors. We show the connection of offset and gain mismatches to nonlinearity mismatches and reveal the two error sources of timing mismatches.

Bloomier Filters: A second look

Denis Charles — 2008-07-09T03:58:07-00:00

(6 Jul 2008)

A Bloom filter is a space efficient structure for storing static sets, where the space efficiency is gained at the expense of a small probability of false-positives. A Bloomier filter generalizes a Bloom filter to compactly store a function with a static support. In this article we give a simple construction of a Bloomier filter. The construction is linear in space and requires constant time to evaluate. The creation of our Bloomier filter takes linear time which is faster than the existing construction. We show how one can improve the space utilization further at the cost of increasing the time for creating the data structure.

Retouched Bloom Filters: Allowing Networked Applications to Flexibly Trade Off False Positives Against False Negatives

Benoit Donnet — 2008-07-15T21:17:34-00:00

(1 Dec 2006)

Where distributed agents must share voluminous set membership information, Bloom filters provide a compact, though lossy, way for them to do so. Numerous recent networking papers have examined the trade-offs between the bandwidth consumed by the transmission of Bloom filters, and the error rate, which takes the form of false positives, and which rises the more the filters are compressed. In this paper, we introduce the retouched Bloom filter (RBF), an extension that makes the Bloom filter more flexible by permitting the removal of selected false positives at the expense of generating random false negatives. We analytically show that RBFs created through a random process maintain an overall error rate, expressed as a combination of the false positive rate and the false negative rate, that is equal to the false positive rate of the corresponding Bloom filters. We further provide some simple heuristics and improved algorithms that decrease the false positive rate more than than the corresponding increase in the false negative rate, when creating RBFs. Finally, we demonstrate the advantages of an RBF over a Bloom filter in a distributed network topology measurement application, where information about large stop sets must be shared among route tracing monitors.

The significance of zonation in a denitrifying, phosphorus removing biofilm

CM Falkentoft — 2008-02-04T18:44:02-00:00

Water Research, Vol. 33, No. 15. (October 1999), pp. 3303-3310.

A biofilm for simultaneous removal of N and P was developed using a continuous lab-scale setup alternating between anaerobic and anoxic conditions. BIOSTYR was used as carrier material. Results showed an exponential increase in initial anaerobic P-release rate for the first month and subsequently a constant rate. The theory of and 0 order of reaction in the bulk water depending on penetration depth into the film was verified for anaerobic P-release using batch tests. Stoichiometric coefficients were for anaerobic P-release to COD-uptake 0.25 g P/g COD and for anoxic P-uptake to nitrate removal 0.06 mol P/mol e-. Both values are low compared to the literature for enriched denitrifying cultures which is taken as an indication of the presence of competing bacteria with the capacity of storing COD. Since the values did not change during the build up period it appears that the competing bacteria survive well with the continuous alternating mode of operation.

Modeling biofilm accumulation and mass transport in a porous medium under high substrate loading

O Wanner — 2008-02-04T14:27:59-00:00

Biotechnology and Bioengineering, Vol. 47, No. 6. (1995), pp. 703-712.

A packed bed biofilm reactor inoculated with pure culture Pseudomonas aeruginosa was run under high substrate loading and constant flow rate conditions. The 3.1-cm-diameter cylindrical reactor was 5 cm in length and packed with 1-mm glass beads. Daily observations of biofilm thickness, influent and effluent glucose substrate concentration, and effluent dissolved and total organic carbon were made during the 13-day experiment. Biofilm thickness appeared to rech quasi-steady-state condition after 10 days. A published biofilm process simulation program (AQUASIM) was used to analyze experimental data. Comparison of observed and simulated variables revealed three distinct phases of biofilm accumulation during the experiment: an initial phase, a growth phase, and a mature biofilm phase. Different combinations of biofilm and mass transport process variables were found to be important during each phase. Biofilm detachment was highly correlated with shear at the biofilm surface during all three phases of biofilm development. © 1995 John Wiley & Sons, Inc.

Hydrolysis of organic wastewater particles in laboratory scale and pilot scale biofilm reactors under anoxic and aerobic conditions

KF Janning — 2008-02-05T12:56:06-00:00

Water Science and Technology, Vol. 38, No. 8-9. (20 November 1998), pp. 179-188.

Hydrolysis and degradation of particulate organic matter has been isolated and investigated in laboratory scale and pilot scale biofilters. Wastewater was supplied to biofilm reactors in order to accumulate particulates from wastewater in the filter. When synthetic wastewater with no organic matter was supplied to the reactors, hydrolysis of the particulates was the only process occurring. Results from the laboratory scale experiments under aerobic conditions with pre-settled wastewater show that the initial removal rate is high: rV,O2 = 2.1 kg O2/(m3 d) though fast declining towards a much slower rate. A mass balance of carbon (TOC/TIC) shows that only 10% of the accumulated TOC was transformed to TIC during the 12 hour long experiment. The pilot scale hydrolysis experiment was performed in a new type of biofilm reactor -- the B2A(R) biofilter that is characterised by a series of decreasing sized granular media (80-2.5 mm). When hydrolysis experiments were performed on the anoxic pilot biofilter with pre-screened wastewater particulates as carbon source, a rapid (rV, NO3=0.7 kg NO3-N/(m3 d)) and a slowler (rV, NO3 = 0.3 kg NO3-N/(m3 d)) removal rate were observed at an oxygen concentration of 3.5 mg O2/l. It was found that the pilot biofilter could retain significant amounts of particulate organic matter, reducing the porosity of the filter media of an average from 0.35 to 0.11. A mass balance of carbon shows that up to 40% of the total incoming TOC accumulates in the filter at high flow rates. Only up to 15% of the accumulated TOC was transformed to TIC during the 24 hour long experiment.

Comment on "degradation of non-diffusible organic matter in biofilm reactors" by and , Wat. Res. 27, 1689-1691 (1993)

Kyoung Ro — 2008-02-05T12:51:12-00:00

Water Research, Vol. 29, No. 1. (January 1995), 387.