![Fig. 1. Topology of the KIII network. Adapted from [Chang & Freeman, 1998a].](/figures/fig-1-topology-of-the-kiii-network-adapted-from-chang-317bh99r.webp)
Q1. What have the authors contributed in "A study on a bionic pattern classifier based on olfactory neural system" ?
In this paper, the authors proposed a new application example of the KIII network for recognition of handwriting numerals.
A study on a bionic pattern classifier based on olfactory neural system
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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.Abstract:
This paper presents a simulation of a biological olfactory neural system with a KIII set, which is a high-dimensional chaotic neural network. The KIII set differs from conventional artificial neural networks by use of chaotic attractors for memory locations that are accessed by, chaotic trajectories. It was designed to simulate the patterns of action potentials and EEG waveforms observed in electrophysiological experiments, and has proved its utility as a model for biological intelligence in pattern classification. An application to recognition of handwritten numerals is presented here, in which the classification performance of the KIII network under different noise levels was investigated.read more
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Journal ArticleDOI
A Class Identification Method Using Freeman’s Olfactory KIII Model
TL;DR: This study proposes a high performance feature extraction method in the classification using Freeman’s olfactory KIII model, making use of the cepstrum analysis often used in speech recognition field and verified that the proposed method is superior to the conventional method.
Proceedings ArticleDOI
Improved KIII model and its application
TL;DR: The improved KIII model can make prediction with confidence measure and credibility measure, not just bare prediction, which also can control the risk of error effectively.
Book ChapterDOI
Chaotic neocortical dynamics.
TL;DR: Stochastic chaos as mentioned in this paper is a hybrid form of stochastic chaos, which is stabilized by additive noise modeled on noise sources in the sensory systems, and it provides tools for succinct empirical models of cortical dynamics performing the most basic cognitive operations: generalization, abstraction and categorization in constructing knowledge.
Proceedings ArticleDOI
On Color Texture Generating Based on Simplified KIII Model
TL;DR: In this paper, a color texture generating algorithm is proposed combining with RGB, where the tricolor of each pixel (red, green and blue) is used as the model input and the model output is composed as the corresponding pixel in generated texture image.
Proceedings ArticleDOI
Analysis of bionic olfactory neural networks based on small-world networks view
TL;DR: Structural characteristics of KIII model, which simulates the whole olfactory neural system and has novel characters different from conventional artificial neural networks, are analyzed and show some interesting results.
References
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Journal ArticleDOI
Chaotic resonance — methods and applications for robust classification of noisy and variable patterns
Robert Kozma,Walter J. Freeman +1 more
TL;DR: A theory of stochastic chaos is developed, in which aperiodic outputs with 1/f2 spectra are formed by the interaction of globally connected nodes that are individually governed by point attractors under perturbation by continuous white noise.
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