FAQ

Neural coding

Known as: Population code, Independent-spike encoding, NeuroElectroDynamics 
Neural coding is a neuroscience related field concerned with characterizing the relationship between the stimulus and the individual or ensemble… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

1959-2017
020040060019592017

Related topics

Related topics

32 relations
Action potentialAnalog signalArtificial neural networkAutoencoder
(More)

Related mentions per year

Related mentions per year

1939-2018
19401960198020002020
Neural coding
Artificial neural network
Wavelet
Deep learning
Action potential
Vector quantization

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2015
Review
2015
A survey: Several technologies of non-orthogonal transmission for 5G
One key advantage of 4G OFDM system is the relatively simple receiver implementation due to the orthogonal resource allocation… (More)
  • table I
  • table II
Is this relevant?
Highly Cited
2010
Highly Cited
2010
Locality-constrained Linear Coding for image classification
The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification… (More)
  • figure 1
  • figure 2
  • table 2
  • table 1
  • figure 3
Is this relevant?
Highly Cited
2009
Highly Cited
2009
Online dictionary learning for sparse coding
Sparse coding---that is, modelling data vectors as sparse linear combinations of basis elements---is widely used in machine… (More)
Is this relevant?
Highly Cited
2008
Highly Cited
2008
Sparse Coding via Thresholding and Local Competition in Neural Circuits
While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
2006
Highly Cited
2006
Efficient sparse coding algorithms
Sparse coding provides a class of algorithms for finding succinct representations of stimuli; given only unlabeled input data, it… (More)
  • table 1
  • table 2
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
Highly Cited
2006
Highly Cited
2006
K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete… (More)
  • figure 2
  • figure 4
  • figure 3
  • figure 5
  • figure 6
Is this relevant?
Highly Cited
2002
Highly Cited
2002
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment… (More)
  • figure 1
  • figure 2
  • figure 4
  • figure 5
  • figure 6
Is this relevant?
Highly Cited
2001
Highly Cited
2001
Rate Coding Versus Temporal Order Coding: What the Retinal Ganglion Cells Tell the Visual Cortex
It is often supposed that the messages sent to the visual cortex by the retinal ganglion cells are encoded by the mean firing… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
2001
2001
Information Distortion and Neural Coding
Our main interest is the question of how neural ensemble activity represents sensory stimuli. In this paper we discuss a new… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Is this relevant?
Highly Cited
1989
Highly Cited
1989
Reading a Neural Code
Traditional approaches to neural coding characterize the encoding of known stimuli in average neural responses. Organisms face… (More)
Is this relevant?