生物神经网络

该方法用Grossberg的生物神经网络实现移动机器人的局部环境建模，将滚动窗口的概念引入到局部路径规划，由启发式算法决定滚动窗口内的局域路径规划目标。

The local environment of mobile robot is modeled with Grossberg 's biological neural networks . The concept of rolling window is introduced into local path planning , and the local path planning goal in the rolling window can be determined by heuristic searching methods .

生物神经网络计算机仿真中数学建模与信号处理

Mathematical Modeling and Signal Processing in Computer Simulation for Biological Neural Networks

脉冲耦合神经网络（PulseCoupledNeuralNetwork，简称PCNN）作为第三代人工神经网络，比传统人工神经网络更好地模仿了生物神经网络，尤其适合图像处理，是目前的研究热点和重点。

As the third generation neural network , Pulse Coupled Neural Network ( PCNN ), which especially suits image processing , imitates biology neural network better compared with traditional neural network .

新型神经元模型及生物神经网络模拟实现算法

A New Model of Biological Neuron and a Mathematical Method of Neural Network

生物神经网络信息加工机理研究的动向与展望

Trends and Prospects on the research of information processing mechanisms of the biological neural network

交流刺激下具有侧向抑制机制的加权小世界生物神经网络的兴奋特性研究

Study under AC Stimulation on Excitation Properties of Weighted Small-World Biological Neural Networks with Side-Inhibition Mechanism

同时，还指出了这种并行推理机与生物神经网络计算的相似性。

Meanwhile , the computing similarities between the parallel inference machine and biological neural networks are also revealed .

一种新的校正铂电阻传感器非线性的数学方法新型神经元模型及生物神经网络模拟实现算法

Novel mathematical method for calibrating nonlinearity of platinum resistance transducers A New Model of Biological Neuron and a Mathematical Method of Neural Network

通过对生物神经网络相关知识的学习，有助于更深入地去学习和理解人工神经元的构成及其工作原理。

Based on the biological neural network knowledge learning , contribute more to learn and understand the structure and work principle of artificial neurons .

而神经网络则是用工程技术手段模拟生物神经网络的结构特征和功能特征的一类人工系统。

Artificial neural network is one of artificial system , which simulates structural and functional characteristics of biological neural network resorted to engineering technological means .

生物神经网络是具有特殊功能的复杂系统，能够产生和传递信息，它是生物医学领域研究的重要内容。

Biological neural network is a complex system with special functions and able to generate and transmit information . It is an important content of biomedical research .

另外，就真实的生物神经网络而言，不考虑突触动力学就无法了解神经编码和神经信息处理。

On the other hand , for real biological networks , we can not understand neuronal coding and neuronal information processing without taking into account synaptic dynamics .

在计算神经科学领域，研究者们试图基于单个神经元的数学模型，通过参数辨识建立更准确的生物神经网络系统。

In the field of computational neuroscience , based on mathematical model of single neurons , researchers try to establish more accurate biological neural network systems by parameter identification .

这主要是因为生物神经网络具有巨大的并行性，即所有的神经能同时工作。

This is mainly because of the huge parallel functional potential of the biological neural network , that is , all neural cells can work at the same time .

并且从目前已有的对生物神经网络的研究结果表明：小世界网络模型的和真实的人脑的神经元网络模型具有最为接近的特征。

At present , the study of biological neural networks shows that the small world network model and the real human brain neuron network model have the closest characteristics .

人工神经网络是以数学手段来模拟人脑神经元网络结构的模型，实现了对生物神经网络的模拟和近似。

Artificial neural network is a kind of model which simulates the human neural network based on mathematical tools , which realize the simulation and approximate of biological neural networks .

其次，将人工神经网络和生物神经网络进行比较，阐述了人工神经网络的工作原理，以及常用的神经网络的模型。

Secondly , the artificial neural networks and biological neural networks are compared , explained the working principle of the artificial neural networks , and the common neural network model .

生物神经网络由众多的生物神经元通过突触耦合组成，是目前发现的最复杂的非线性网络系统之一。

Biological neural network is composed of a large number of biological neurons coupled by synapses , and is found to be one of the most complex non-linear network systems .

我们知道真实的生物神经网络满足小世界网络结构，具有短路径长度和大聚类系数的特性。

It is well known that the neural network has a short path length and large clustering coefficient , namely real biological neural network module meet the small-world network structure .

神经网络的多稳定性，实质上体现了网络中神经元活动的群体计算特征，更深层次地揭示了生物神经网络的内在本质，具有更强大的计算能力。

The multistability essentially characterizes the group properties of neurons and deeply depicts the neural networks in essence , so the multistable neural networks have more powerful parallel computational capability .

本文用我们所提出的一种简化现实性神经网络模型〔1〕所构造的时滞非线性振子网络〔2〕，模拟生物神经网络的同步振荡活动。

In this paper , the synchronous oscillatory activities of the biological neural network were simulated with a network of delayed nonlinear oscillators based on our simplifying realistic neural network model ;

同时，由于生物神经网络的复杂性，实验条件和手段的局限，实验数据总是有限且不完整。

At the same time , due to the complexity of biological neural network , the limitations of experimental conditions and means , the experimental data is always limited and incomplete .

主要的研究工作如下：第一、在对生物神经网络认识的基础上，对人工神经网络进行了系统的综述。

The main points of research are as follows : First of all , on the basis of the analysis of the biological neural networks , the back-propagation networks are expounded systematically .

由于生物神经网络是具有反馈的非线性系统，为分析生物神经网络，人们只能在一定的控制条件下获得相应的实验数据。

Because of the biological neural network is a nonlinear system with feedback , for the analysis of biological neural network , people can only under certain controlled conditions to obtain the corresponding experimental data .

它具有高度的非线性，是可以实现复杂的逻辑操作和非线性映射的系统，在其中信息的传播、存贮方式都与生物神经网络相似。

Artificial Neural Network in which the transmission and storage methods of information are similar to that in biological neural networks is nonlinear , and is the system which is able to perform complex logic operations and non-linear mapping .

随着大量的实验数据的不断积累，神经生物学家认识到仅由详细的神经系统生理学和解剖学的数据难以理解和推断生物神经网络的生化组成、生理结构和作用机理。

With the large amount of experimental data continue to accumulate , Neurobiologists have recognized that only by the detailed data of anatomy and physiology of nervous system is difficult to understand and extrapolate the biochemical composition , physical structure and mechanism of biological neural network .

改进的生物激励神经网络的机器人路径规划

Neural Net Robot Path Planning of Modified Biologically Inspired Neural Networks

生物激励神经网络路径规划仿真研究与改进

Simulation Research and Improvement on Biologically Inspired Neural Network Path Planning

生物仿真神经网络图像分割方法中的参数自动确定

Automatic Setting the Parameters of Emulational Biology Neural Network

介绍了基于生物激励神经网络的移动机器人路径规划。

The biologically inspired neural networks based path planning approaches of mobile robot were introduced .