Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication Export

@article{citeulike:1372119, abstract = {We present a method for learning nonlinear systems, echo state networks (ESNs). ESNs employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains. The learning method is computationally efficient and easy to use. On a benchmark task of predicting a chaotic time series, accuracy is improved by a factor of 2400 over previous techniques. The potential for engineering applications is illustrated by equalizing a communication channel, where the signal error rate is improved by two orders of magnitude. 10.1126/science.1091277}, author = {Jaeger, Herbert and Haas, Harald}, citeulike-article-id = {1372119}, citeulike-linkout-0 = {http://dx.doi.org/10.1126/science.1091277}, citeulike-linkout-1 = {http://www.sciencemag.org/cgi/content/abstract/304/5667/78}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/15064413}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=15064413}, day = {2}, doi = {10.1126/science.1091277}, journal = {Science}, keywords = {connectionism-essay}, month = {April}, number = {5667}, pages = {78--80}, posted-at = {2009-05-14 23:48:48}, priority = {2}, title = {Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication}, url = {http://dx.doi.org/10.1126/science.1091277}, volume = {304}, year = {2004} }

TY - JOUR ID - citeulike:1372119 L3 - citeulike-article-id:1372119 N2 - We present a method for learning nonlinear systems, echo state networks (ESNs). ESNs employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains. The learning method is computationally efficient and easy to use. On a benchmark task of predicting a chaotic time series, accuracy is improved by a factor of 2400 over previous techniques. The potential for engineering applications is illustrated by equalizing a communication channel, where the signal error rate is improved by two orders of magnitude. 10.1126/science.1091277 IS - 5667 JF - Science EP - 80 TI - Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication VL - 304 SP - 78 KW - connectionism-essay AU - Jaeger, Herbert AU - Haas, Harald PY - 2004/04/02/ UR - http://dx.doi.org/10.1126/science.1091277 ER -