• Publications
  • Influence
Optimal unsupervised learning in a single-layer linear feedforward neural network
TLDR
An optimality principle is proposed which is based upon preserving maximal information in the output units and an algorithm for unsupervised learning based upon a Hebbian learning rule, which achieves the desired optimality is presented. Expand
Harnessing neuroplasticity for clinical applications
TLDR
Integration of information across disciplines should enhance opportunities for the translation of neuroplasticity and circuit retraining research into effective clinical therapies. Expand
Classification and definition of disorders causing hypertonia in childhood.
TLDR
The purpose of the workshop and this article are to define the terms "spasticity," "dystonia," and "rigidity" as they are used to describe clinical features of hypertonia in children to allow differentiation of clinical features even when more than 1 is present simultaneously. Expand
Definition and classification of hyperkinetic movements in childhood
Hyperkinetic movements are unwanted or excess movements that are frequently seen in children with neurologic disorders. They are an important clinical finding with significant implications forExpand
Stereo disparity computation using Gabor filters
  • T. Sanger
  • Mathematics
  • Biological Cybernetics
  • 1 October 1988
A solution to the correspondence problem for stereopsis is proposed using the differences in the complex phase of local spatial frequency components. One-dimensional spatial Gabor filters (GaborExpand
Bayesian filtering of myoelectric signals.
  • T. Sanger
  • Computer Science, Medicine
  • Journal of neurophysiology
  • 1 February 2007
TLDR
Use of the nonlinear filter significantly reduces noise compared with current algorithms, and it may therefore permit more effective use of the EMG signal for prosthetic control, biofeedback, and neurophysiology research. Expand
Probability density estimation for the interpretation of neural population codes.
  • T. Sanger
  • Mathematics, Medicine
  • Journal of neurophysiology
  • 1 October 1996
TLDR
Simulations show that density estimation correctly finds movement directions for nonuniform distributions of preferred directions and noncosine cell tuning curves, whereas the population vector method fails for these cases. Expand
A tree-structured adaptive network for function approximation in high-dimensional spaces
  • T. Sanger
  • Mathematics, Computer Science
  • IEEE Trans. Neural Networks
  • 1 March 1991
TLDR
The author proposes a technique based on the idea that for most of the data, only a few dimensions of the input may be necessary to compute the desired output function, and it can be used to reduce the number of required measurements in situations where there is a cost associated with sensing. Expand
Theoretical Considerations for the Analysis of Population Coding in Motor Cortex
  • T. Sanger
  • Computer Science, Psychology
  • Neural Computation
  • 15 November 1999
TLDR
It is shown here that such a population vector can always be found given a very general set of assumptions and constitutes only weak support for the explicit use of a particular coordinate representation by motor cortex. Expand
Neural population codes
  • T. Sanger
  • Medicine, Computer Science
  • Current Opinion in Neurobiology
  • 1 April 2003
TLDR
It is shown that for population codes based on neurons that have a Poisson distribution of spike probabilities, the behavior and computational properties of the code can be understood in terms of the tuning properties of individual cells. Expand
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