recognition network

The classifier is a multi-module neural network, so the conflict between the scale of BP network and the complexity of recognition tasks can be transformed to the conflict between the scale of recognition system and the complexity of recognition tasks.

同时，分类器采用多神经网络模块结构，将以往BP网络规模大小与问题复杂性的矛盾转化为系统规模大小与问题复杂性的矛盾。

BP neural network is used for face orientation recognition and a sub network with a set of single export is replaced with formerly BP neural network to increase the accuracy of face orientation recognition.

把BP网络用于人脸朝向的识别，并且用一组单输出的子网络代替原来的BP网络，提高了人脸朝向的识别率。

A compensative fuzzy classifier based on genetic algorithm wavelet neural network is presented to solve the problem like high-dimensional biometric authentication such as voiceprint and face recognition. The experiment result proved that the classifier could effectively improve the recognition rate comparing to the traditional Back-Propagation neural network.

针对声纹识别和人脸识别等高维的生物特征身份识别问题，本文提出了一种基于遗传小波神经网络的补偿模糊分类器，实验结果表明本分类器比传统的BP神经网络的效果好。

In order to improve the recognition performance of synergetic neural network further, a hierachical synergetic neural network model for multifont character recognition was proposed.

提出了一种用于多字体字符识别的分级协同神经网络模型。

But database safety is not come in for recognition as same as OS and network.

但是数据库通常没有象操作系统和网络这样在安全性上受到重视。

Design of Handwritten Electronic Symbol Recognition Based on BP Neural Network graphic-art technique

基于BP神经网络的手绘电路图形符号识别技术

Vehicle License Plate Recognition Algorithm Based on Moving Target Location and Compound Neural Network

基于移动窗口定位和复合神经网络的车牌识别算法

The neural network based on the biomimetic pattern recognition principles is built.

运用仿生模式识别理论建立起识别神经网络模型。

The Adaptive Time-delay Neural Network ( ATNN) based on exo-atmospheric space point target IR radiation sequences is proposed in order to improve the recognition rate.

为提高目标的正确识别率，提出一种基于空间点目标红外辐射序列的自适应时延神经网络（ATNN）识别方法。

The ability of neural networks to deal with time dynamic signal was improved with a new neural network architecture specializing in syllable recognition based on the time delay neural network ( TDNN) and the convolutional neural network.

为了提高人工神经网络处理动态信号能力，在时延神经网络（TDNN）和卷积神经网络（CNN）的基础上，针对孤立音节的特点，提出了一个新的网络结构，研究了其学习算法。