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MATLAB2维小波变换经典程序，用DWT实现二维小波变换(MATLAB2-dimensional wavelet transform classical procedures, with the realization of two-dimensional wavelet transform DWT)

Stewart platform, classic model with PID controller

时差法在超声波测量流量中的应用程序,原吗利用相关法求得时差(time difference in ultrasonic flow measurement applications, the original use of the relevant law? Seek TDOA)

Bloch simulator. [mx,my,mz] = bloch(b1,gr,tp,t1,t2,df,dp,mode,mx,my,mz) Bloch simulation of rotations due to B1, gradient and off-resonance, including relaxation effects. At each time point, the rotation matrix and decay matrix are calculated. Simulation can simulate the steady-state if the sequence is applied repeatedly, or the magnetization starting at m0. INPUT: b1 = (Mx1) RF pulse in G. Can be complex. gr = (Mx1,2,or 3) 1,2 or 3-dimensional gradient in G/cm. tp = (Mx1) time duration of each b1 and gr point, in seconds, or 1x1 time step if constant for all points

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Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

asfig function for wavelet processing in wavelab

现有一个信号：x(n)=1+cos(π*n/4)+ cos(2*π*n/3)设计及各种数字滤波器以达下列目的： 低通滤波器，滤除cos(2*π*n/3) 的成分，即想保留的成分为1+cos(π*n/4) 高通滤波器，滤除1+cos(π*n/4) 的成分，即想保留的成分为cos(2*π*n/3) 带通滤波器，滤除1+cos(2*π*n/3) 的成分，即想保留的成分为cos(π*n/4) 带阻滤波器，滤除cos(π*n/4) 的成分，即想保留的成分为1+cos(2*π*n/3) 1. 用MATLAB命令butterord求除滤波器的阶数,用命令butter设计各滤波器；画出滤波器幅度和相频相应 取各滤波器的系统函数H(z)。 (an existing signal : x (n) = a cos (* n/4) cos (2** n/3) design and digital filter to achieve the following objectives : low-pass filter, filter cos (2** n/3) the ingredients that want to retain an element of a cos (* n/4) high-pass filter, a filter cos (* n/4) components, namely to retain the element of cos (2** n/3) band-pass filter , a filter cos (2** n/3) components, namely to retain the element of cos (* n/4) band stop filter, the filter cos (* n/4) components, namely to retain the ingredients for a cos ( 2** n/3) 1. MATLAB order butterord except for the band Filter, using the order of the filter design butter; paint Filter magnitude and phase frequency of the corresponding filter system function H (z).)

fiber matlab programme

VIEW3D GUI for interactive viewing of 3D Volumes in matlab