NDLI: Entropy-based stochastic gradient algorithm with adaptive neuron slope for all-pole whitening

Content Provider	IET Digital Library
Author	Krstić, V. R.
Abstract	The stochastic gradient algorithm presented employs the time-varying neuron's slope to optimise performing of the all-pole filter-whitener maximising the joint Shannon's entropy. By using the time adaptive slope, which matches the unknown probability density function of an input process, a neuron slope selection issue of the original algorithm is facilitated and its tracking of non-stationary statistics is improved. The performing of algorithm is verified using the whitener as a front-end amplitude equaliser of the blind equaliser.
Starting Page	397
Ending Page	399
Page Count	3
ISSN	00135194
Volume Number	52
e-ISSN	1350911X
Issue Number	Issue 5, Mar (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/52/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2015.3052
Journal	Electronics Letters
Publisher Date	2016-01-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Neuron Slope All-pole Filter-whitener Blind Equaliser Blind Equalisers Communication Channel Equalisation And Identification Entropy Entropy-based Stochastic Gradient Algorithm Filtering Method in Signal Processing Filtering Theory Front-end Amplitude Equaliser Nonstationary Statistics Probability Shannon Entropy Signal Processing Theory Statistics Time Adaptive Slope Time-varying Neuron Slope Unknown Probability Density Function
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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