WG15W_16AK_STD_STO15-1_80F7_091202

program on image processing based on MATLAB for biometric recognition

一本非常有价值的MAtlab编程参考书，值得一看。(A very valuable reference book MAtlab programming, worth a visit.)

simulink入门教程，从零开始，学习的好材料(simulink introductory tutorial, starting from scratch, learning materials)

小波变换在图像压缩中的应用，都是完整的论文，希望能对大家有所帮助(Wavelet transform in image compression, are full of papers, hoping to be helpful)

说明：  这里介绍了一种基于自适应滤波的噪声抵消法，采用归一化最小均方误差算法，采集实际噪声环境下各种不同信噪比的带噪语音样本进行降噪处理，实验结果表明，处理后信号的信噪比得到了较大程度的提高，大大改善了听音效果，具有很高的可懂度，且语音自然度好，没有失真；并与谱减法进行了比较，自适应噪声抵消法的降噪幅度比谱减法有一定提高，在听音效果上，用自适应噪声抵消法处理后的语音在清晰度，自然度方面优于谱减法。(Here a novel adaptive noise cancellation method using normalized least mean square algorithm, collecting a variety of actual noise environment, the SNR of noisy speech samples for noise reduction, experimental results show that treatment After the signal to noise ratio was greater improvement in the level, greatly improved the listening results, with high intelligibility and naturalness of speech is good, no distortion and were compared with the spectral subtraction, adaptive noise cancellation law than the spectral subtraction noise reduction rate of a certain improvement in the listening results, and with the adaptive noise cancellation method in the treatment of voice clarity, naturalness is better than spectral subtraction.)

利用模板对图像进行增强，主要用于对道路的增强处理，所用模板是适应予道路增强的，当然可以自己根据自己需要进行修改(use templates to enhance the images, mainly for the increase of road, template is used to meet the increasing road course according to their own need for amendment)

adaptive binary arithmetic coding (CABAC) is a method of entropy coding first introduced in H.264/AVC and now used in the newest standard High Efficiency Video Coding (HEVC).

慢特征分析 sfa matlb源程序 参考文献： Wiskott, L. and Sejnowski, T.J. (2002), "Slow Feature Analysis: Unsupervised Learning of Invariances",(Slow feature analysis SFA MATLB source program)

说明：  模式识别中人连识别眼镜定位，用的是matlab支持向量机开发的(human pattern recognition to identify even glasses positioning, using the Matlab SVM Development)

无线传感器网络定位用到的无线传输模型 Regular Model, Logarithmic Attenuation Model, DOI Model, RIM Model (Wireless sensor network localization using wireless transmission model, Regular Model, Logarithmic Attenuation Model, DOI Model, RIM Model Achieve functional distance and transmission attenuation swap ~~~~~~~~~~~~~~~~~~~~~~Regular Model~~~~~~~~~~~~~~~ In this model, the radio range is a circle ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ReceivedSignalStrength=SendingPower-PathLoss e.g, RSS=Pt-Pl(d0)-10*η*log10(dist/d0) Pt:transmit power pl(d0):the pass loss for a reference distance of d0 ηis the path loss exponent above parameters are saved in ../Parameters_Of_Models.mat dist:distance between sender and receiver(m) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ typical value:Pt=0-4dBm(max),Pl(d0)=55dB(d0=1m),η(2~4)=4(indoor,outdoor) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~Logarithmic Attenuation Model~~~~~~~~~ In this model, the radio range is a circle ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ReceivedSignal)