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Abstract: Recently there has been increased interest in high speed adaptive filtering where the usual stochastic gradient or least mean-square (LMS) algorithm is replaced with the simpler algorithm where adaptation is guided only by the polarity of the error signal.
Gersho, “Adaptive filtering with binary reinforcement,” Int. Symp. Inform. Theory, Asilomar, CA, 1972. W. Feller, An Introduction to Probability Theory and ...
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Adaptive filtering with binary reinforcement. Gersho, A. IEEE Transactions on Information Theory 30(2): 191-199. ISSN: 0018-9448. 1984. DOI: 10.1109/tit ...
May 22, 2016 · YES! The solution to this problem exists in the literature. Its called Denoising Autoencoder. It belongs to a class of neural networks namely 'AutoEncoder's.
The adaptive filtering sign algorithm is analyzed in the case of nonstationary and correlated data and it is proved that the EAAE is the sum of two terms ...
Gersho, ''Adaptive Filtering with Binary Reinforcement,'' IEEE Trans. IT-. 30, 191–199 (March 1984). 11. T. Claasen and W. Mecklenbrauker, ''Comparison of ...
Feb 27, 2012 · It finds out the difference between input and output and using the error function and previous coefficients finds out the new filter coefficients.
Missing: binary reinforcement.
This paper introduces new methods in system identification with binary-valued output observations. It resolves two key issues, (a) regression structures for ...
This paper presents a new spline adaptive filtering (SAF) algorithm based on signed regressor (SR) of input signal. The algorithm is called SR-SAF ...
Nov 15, 2005 · Gersho, “Adaptive Filtering with Binary Reinforcement,” IEEE Transactions on Information Theory, vol. IT-30, no. 2, pp. 191–199, March 1984 ...