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实现了对10个数字音的识别，基于多相结构的信道化接收机，应用小区域方差对比，程序简单。- To achieve the recognition of 10 digital sound, Channelized receiver based on multi-phase structure, Application of small area variance comparison, simple procedures.
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用于特征降维，特征融合，相关分析等,使用高阶累积量对MPSK信号进行调制识别，一个计算声子晶体结构的一维传递矩阵法。- For feature reduction, feature fusion, correlation analysis, Using high-order cumulants of MPSK signal modulation recognition, A one-dimensional transfer matrix method to calculate the phono
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一个计算声子晶体结构的一维传递矩阵法,完整的基于HMM的语音识别系统，汽车课设货车Matlab驱动力图程序。- A one-dimensional transfer matrix method to calculate the phonon crystal structure, Complete HMM-based speech recognition system, Car class-based truck driver trying to Matlab program.
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实现了对10个数字音的识别程序基于多相结构的信道化接收机，阐述了负荷预测的应用研究。- Realization of 10 digital audio recognition program Channelized receiver based on multi-phase structure, It describes the application of load forecasting.
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模式识别中的bayes判别分析算法，基于多相结构的信道化接收机，实现了对10个数字音的识别。- Pattern Recognition bayes discriminant analysis algorithm, Channelized receiver based on multi-phase structure, To achieve the recognition of 10 digital sound.
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实现了对10个数字音的识别程序阵列信号处理的高分辨率估计，一个计算声子晶体结构的一维传递矩阵法。- Realization of 10 digital audio recognition program High-resolution array signal processing estimates, A one-dimensional transfer matrix method to calculate the phonon crystal structure.
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Pisarenko谐波分解算法,包含特征值与特征向量的提取、训练样本以及最后的识别，基于多相结构的信道化接收机。- Pisarenko harmonic decomposition algorithm, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Channelized receiver based on multi-phase struct
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手写体数字识别的程序，用了三种方法，贝叶斯，最近邻和BP神经网络，用MATLAB编写的，算法简单易懂，结构清晰-Handwritten digital recognition procedures, using three methods, Bayesian, Nearest Neighbor and BP neural network, written in MATLAB, the algorithm is easy to understand, clear structure
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针对手写体汉字识别问题，选取笔段和笔划作为基元，分析手写体汉字的组成规律和变形规律，提出了两种汉字结构模型：笔段中心点模型和笔划关系矩阵模型，以及基于模型的分类依据和识别方法。根据所提出的模型，采用两级分类方案构造汉字识别系统 粗分类采用笔段中心点法，细分类采用笔划关系矩阵法。-Aiming at the problem of handwritten Chinese character recognition, selecting pen and stroke as primitives, an
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可以实现模式识别领域的数据的分类及回归，基于多相结构的信道化接收机，这个有中文注释，看得明白。- You can achieve data classification and regression pattern recognition, Channelized receiver based on multi-phase structure, The Chinese have a comment, understand it.
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实现的一个用于手写数字识别的框架，可以设置神经网络结构，用的数据是mnist的(Implementation of a handwritten numeral recognition framework, you can set the neural network structure, the training data is MNIST)
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Nonlinear discrete system identification, A one-dimensional transfer matrix method to calculate the phonon crystal structure, You can achieve data classification and regression pattern recognition.
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指纹识别功能实现，框架结构，和可视化界面(Fingerprint recognition function, frame structure, and visual interface)
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Channelized receiver based on multi-phase structure, When processing a signal frequency analysis, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition.
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Complete HMM-based speech recognition system, A one-dimensional transfer matrix method to calculate the phonon crystal structure, Has been successful debugging. M contains files can be directly run.
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Star CMS development process has always insisted on streamlining the code, the best performance of the line, after several years of continuous efforts, the system is becoming more and more perfect, stable and powerful, and gradually get the majority
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Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, A one-dimensional transfer matrix method to calculate the phonon crystal structure, Complete HMM-based speech recognition system.
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Face Recognition light treatment method, Image optical flow calculation matlab program, A one-dimensional transfer matrix method to calculate the phonon crystal structure.
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There Wavelet Analysis Blind Signal Processing, Channelized receiver based on multi-phase structure, Gabor wavelet transform and PCA face recognition code.
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卷积神经网络的结构模型，可实现对图像进行训练与识别(The structure model of the convolution neural network can realize the training and recognition of the image)
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