搜索资源列表
wav_featu
- 模式识别中，以小波分析为基础的信号能量特征提取方法，matlab源代码-pattern recognition to wavelet analysis of the signal energy feature extraction method, the source code Matlab
PronyToolbox
- prony信号处理识别低频振荡模式提取特征根阻尼比
车牌号码识别matlab完整程序实现
- 随这图形图像技术的发展，现在的车牌识别技术准确率越来越高，识别速度越来越快。无论何种形式的车牌识别系统，它们都是由触发、图像采集、图像识别模块、辅助光源和通信模块组成的。车牌识别系统涉及光学、电器、电子控制、数字图像处理、计算视觉、人工智能等多项技术。触发模块负责在车辆到达合适位置时，给出触发信号，控制抓拍。辅助光源提供辅助照明，保证系统在不同的光照条件下都能拍摄到高质量的图像。图像预处理程序对抓拍的图像进行处理，去除噪声，并进行参数调整。然后通过车牌定位、字符识别，最后将识别结果输出。
FastICAmatlabtoolbox.rar
- FastICA的matlat软件包，独立分量分析(ICA)在模式识别（如人脸识别），信号分离等领域有着广泛的应用。 ,The FastICA package for MATLAB The FastICA package is a free (GPL) MATLAB program that implements the fast fixed-point algorithm for independent component analysis and projection pursuit.
xuno_featureextraction
- 用于提取某一信号的特征参数以实现模式识别的分析。-For extracting the characteristic parameters of a signal in order to achieve pattern recognition analysis.
xunobp
- 用bp神经网络对经提取得到的信号特征参数进行信号的模式识别。-Bp neural network used by the signal characteristic parameters were extracted for signal pattern recognition.
xunorbf
- 用rbf神经网络对经提取得到的信号特征参数进行信号的模式识别。-Rbf neural network by using extracted parameters of the signal characteristics of the signal pattern recognition.
xunosvc
- 用支持向量机SVM对经提取得到的信号特征参数进行信号的模式识别。-Support Vector Machines SVM right after the signal characteristic parameters were extracted for signal pattern recognition.
knnsearch
- 寻找测试样本的最近邻，可以有效的用于用于模式识别，信号处理-This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing. The code was initially
DistributedFilberOpticSensorSystem
- 本文基于马赫-泽德干涉结构的分布式光纤传感系统，采用模式识别的思想，详细论述了信号特征辨识和提取方法，提高了定位准确度，减少了误报！-Based on Mach- Zehnder interferometer structure of the distributed optical fiber sensing system, using pattern recognition idea, discussed in detail the signal feature recognition and
DEC5416
- FIR(Finite Impulse Response)滤波器：有限长单位冲激响应滤波器，是数字信号处理系统中最基本的元件，它可以在保证任意幅频特性的同时具有严格的线性相频特性，同时其单位抽样响应是有限长的，因而滤波器是稳定的系统。因此，FIR滤波器在通信、图像处理、模式识别等领域都有着广泛的应用。-FIR (Finite Impulse Response) filters: finite impulse response filter unit, digital signal processi
empirical_mode_decomposition
- 经验模态法可以做信号加强、模式识别、特征提取等,本程序是经验模态的matlab实现，-the realization of emd using matlab.it canbe used in the signal denoising ,pattern recognition and feature extraction
GAOT
- 用mfcc函数实现语音信号的特征提取，对提取数据进行分析 模式识别的一道例题-With MFCC function realization of speech signals to extract feature extraction and analysis of the data and pattern recognition of a sample
Hmm
- 语音识别技术的最终目标是要让计算机能与人自由交谈。目前，连续语音识别技术正趋于成熟，语音识别也延伸出了诸多实用化的研究方向。今后，语音识别的重点将集中在自然话语识别与理解、实时语音识别和语音识别鲁棒性等方面。作为一门交叉学科，语音识别所涉及到的技术有信号处理、模式识别、概率论和信息论、发声机理、听觉机理和人工智能等。-The ultimate goal of speech recognition technology is to make computers and allowing other
four-Toolbox-for-SVM
- SVM分类器,关键是对信号进行分类，是模式识别的必备宝典-SVM classifier, the key is to classify the signal is essential for pattern recognition Collection
CS
- 压缩感知（Compressive Sensing(CS)，或称Compressed Sensing、Compressed Sampling）。该理论指出：对可压缩的信号可通过远低于Nyquist标准的方式进行采样数据，仍能够精确地恢复出原始信号。该理论一经提出，就在信息论、信号/图像处理、医疗成像、模式识别、地质勘探、光学/雷达成像、无线通信等领域受到高度关注，并被美国科技评论评为2007年度十大科技进展。-Compressed Sensing (Compressive Sensing (CS)
信息熵算法
- 基于Matlab平台开发的用于生理信号特征选择的程序算法，信息熵算法，主要用于特征选择，属于模式识别的一类。-The program used for physiological signal feature selection algorithm based on Matlab platform development, information entropy algorithm is mainly used for feature selection, belongs to a class
M_Unitary_esprit
- 酉—esprit信号模式识别算法，可有效辨识信号阶数以及各阶频率、衰减因数、相角、幅值几个参数-Unitary-esprit signal pattern recognition algorithm can effectively identify the signal as well as the rank order of frequency, attenuation factor, phase angle and amplitude of several parameters
DeepLearnToolbox_CNN_lzbV2.0
- DeepLearnToolbox_CNN_lzbV2.0 深度学习,卷积神经网络,Matlab工具箱 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusberg
Matlab-heart-sound-
- 本文综述了心音检测技术以及现代数字信号处理方法(谱估计、联合时一频分析、小波分析、模式识别)在心音信号分析中的应用及研究进展。-Heart sound detection technology are reviewed, and the modern digital signal processing method (spectrum estimation, joint frequency analysis, wavelet analysis and pattern recognition) i