第二届生物计算：理论及应用国际会议会前论文集
出版时间:
2007-09
版次:
1
ISBN:
9787121040993
定价:
120.00
装帧:
平装
开本:
16开
纸张:
胶版纸
页数:
784页
字数:
1450千字
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本书是第二届生物计算：理论及应用国际会议（BIC-TA 2007）会前论文扩展摘要集。“生物计算”是一个内蕴非常丰富的科学概念，是一门跨越包括数学、生物学、计算机科学、物理学、化学、生理学、进化理论和心理学等学科在内的综合学科，是当前国际学术界研究的前沿及热点。BIC-TA系列国际学术会议旨在为国际间从事生物计算及相关领域的专家和学者提供一个交流最新科研成果、探讨未来发展方向的国际论坛。
本书共收集了从近1400篇稿件中所录用的200余篇高水平学术论文的扩展摘要，涉及神经网络、进化计算、分子计算、群体智能、生物计算等多个研究领域的理论及应用研究。对相关研究领域中的本科高年级学生、研究生、教学及科研人员均有较大的帮助。 大会特约报告
On DNA Computer Model
Bio-Inspired and Bio-Mimetic Devices and Systems for Computer Communication with the Human Brain
Capture and Release of Protein by Rversible DNA-induced Sol-gel Transition System
Autonomous DNA computer and its application to genetic diagnosis
Protein Contact Map Prediction Using Evolutionary Optimization Technique
Stochastic modelling of bilogical system: membrane systems in Systems Biology
Membrane Systems: An Unconventional Model for Computation(and Simulation)
Visual Perception and Content-based Image Retrieval
Biologically Inspired Models for Micro-and Nano-Systems Design
上篇 理论和方法
第1部分 神经网络
A New Evolutionary Neural Network Algoithm Based on Improved Genetic Algorithm and its Application in Power Transformer Fault Diagnosis
A Note on Global Exponentially Stability of Neural Networks with Multiple Time Delays
Convergence of Gradient Descet Algorithm for Diagonal Recurrent Neural Networks
Application of Wavelet Neural Networks for Recognizing the Patterns of Wood Inner Defects
A fuzzy Neural Network Model with Confidence Measure for Material Property Prediction
Approximation Capbility to Compact Sets of Functions and Operators by Feedforward Neural Networks
Application of Local Activeity Theory to Chaotic Chemical Reaction Model
On Asympotic Stabhility of Discrete-Time Non-autonomous Delayed Hopfiedld Neural Networks
An LIM Approach to the Global Asympotic Stability for Delayed Cellular Networks
Adaptiv Control for Single-Phase Unified Power Quality Conditioner Using Neural Networks
Redundant Information in Suport Vectors and Data Dependent Method for Imroving SVM Classifier
An Associative Sparse Coding Neural Network and Applications for Recognition
……
下篇 应用
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内容简介:
本书是第二届生物计算：理论及应用国际会议（BIC-TA 2007）会前论文扩展摘要集。“生物计算”是一个内蕴非常丰富的科学概念，是一门跨越包括数学、生物学、计算机科学、物理学、化学、生理学、进化理论和心理学等学科在内的综合学科，是当前国际学术界研究的前沿及热点。BIC-TA系列国际学术会议旨在为国际间从事生物计算及相关领域的专家和学者提供一个交流最新科研成果、探讨未来发展方向的国际论坛。
本书共收集了从近1400篇稿件中所录用的200余篇高水平学术论文的扩展摘要，涉及神经网络、进化计算、分子计算、群体智能、生物计算等多个研究领域的理论及应用研究。对相关研究领域中的本科高年级学生、研究生、教学及科研人员均有较大的帮助。
-
目录:
大会特约报告
On DNA Computer Model
Bio-Inspired and Bio-Mimetic Devices and Systems for Computer Communication with the Human Brain
Capture and Release of Protein by Rversible DNA-induced Sol-gel Transition System
Autonomous DNA computer and its application to genetic diagnosis
Protein Contact Map Prediction Using Evolutionary Optimization Technique
Stochastic modelling of bilogical system: membrane systems in Systems Biology
Membrane Systems: An Unconventional Model for Computation(and Simulation)
Visual Perception and Content-based Image Retrieval
Biologically Inspired Models for Micro-and Nano-Systems Design
上篇 理论和方法
第1部分 神经网络
A New Evolutionary Neural Network Algoithm Based on Improved Genetic Algorithm and its Application in Power Transformer Fault Diagnosis
A Note on Global Exponentially Stability of Neural Networks with Multiple Time Delays
Convergence of Gradient Descet Algorithm for Diagonal Recurrent Neural Networks
Application of Wavelet Neural Networks for Recognizing the Patterns of Wood Inner Defects
A fuzzy Neural Network Model with Confidence Measure for Material Property Prediction
Approximation Capbility to Compact Sets of Functions and Operators by Feedforward Neural Networks
Application of Local Activeity Theory to Chaotic Chemical Reaction Model
On Asympotic Stabhility of Discrete-Time Non-autonomous Delayed Hopfiedld Neural Networks
An LIM Approach to the Global Asympotic Stability for Delayed Cellular Networks
Adaptiv Control for Single-Phase Unified Power Quality Conditioner Using Neural Networks
Redundant Information in Suport Vectors and Data Dependent Method for Imroving SVM Classifier
An Associative Sparse Coding Neural Network and Applications for Recognition
……
下篇 应用
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