Le Wang
Boston University
23 Papers
86 Citations
Le Wang is an academic researcher from Boston University. The author has contributed to research in topics: Chaotic & Artificial neural network. The author has an hindex of 9, co-authored 18 publications. Previous affiliations of Le Wang include Zhejiang University.
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Papers
A study on a bionic pattern classifier based on olfactory neural system
TL;DR: A simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network designed to simulate the patterns of action potentials and EEG waveforms observed in electrophysiological experiments is presented.
Application of chaotic neural model based on olfactory system on pattern recognitions
Guang Li,Zhenguo Lou,Le Wang,Xu Li,Walter J. Freeman +4 more
- 27 Aug 2005
TL;DR: A simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network designed to simulate the patterns of action potentials and EEG waveforms observed in electrophysioloical experiments, is presented.
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Individual Differences in Temporal Perception and Their Implications for Everyday Listening
Barbara G. Shinn-Cunningham,Leonard Varghese,Le Wang,Hari M. Bharadwaj +3 more
- 01 Jan 2017
TL;DR: In this article, the authors review the evidence that behavioral and physiological differences across individual listeners with normal hearing thresholds reflect differences in the number of auditory nerve fibers responding to sound despite normal cochlear mechanical function (cochlear neuropathy).
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A Modeling Study of the Responses of the Lateral Superior Olive to Ipsilateral Sinusoidally Amplitude-Modulated Tones
Le Wang,H. Steven Colburn +1 more
TL;DR: The results support the conclusion that KLT channels may play a major role in the large rate decreases seen in some units and that background inhibition may be a contributing factor, a factor that could be adequate for small decreases.
Extreme learning machine evolved by fuzzified hunger games search for energy and individual thermal comfort optimization
TL;DR: In this paper , a hybrid Extreme Learning Machine-Fuzzified Hunger Games Search model was proposed to solve the issue of unreliable, ill-conditioning, and lacking resilience of ELM.
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