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[matlab] freqz_m DL : 0: 求取系统的绝对幅度响应、相对的db值幅度响应、相位响应和群延时响应的函数％％db为相对振幅(dB) ％mag为绝对振幅％pha为相位响应％grd为群延时％w为频率样本点向量％b为Ha(z)分子多项式系数(对FIR而言，b=h) ％a为Hz(z)分母多项式系数(对FIR而言，a=1) ％-strike rate system in response to the absolute and relative value range db response phase and group delay response to the response function%% db relative amplitude (dB)% mag as the absolute amplitude% of MTS Phase Response% for the group delay grd% w frequency of sample points for the vector b Ha% (z) elements polynomial coefficient (F IR, b = h)% for a Hz (z) denominator polynomial coefficient (right FIR, a = 1)%
Date : 2025-12-29 Size : 1kb User : 吴江华
[matlab] matlabsnakegame DL : 0: The Game: Make the snake grow longer by directing it to the food. Extra bonus points are given from hearts, eat them as fast as possible as amount of bonus points decreases with time. Higher level gives more points for the food but will also make it tougher to steer a long snake as speed increaces. Five different mazes as well as play w/o maze are possible. -The Game : Make the snake grow longer by directing it to the food. Extra bonus points are given from hearts. eat them as fast as possible as amount of bonus po ints decreases with time. Higher level gives mo 're points for the food but will also make it tough er to steer a long snake as speed increaces. Five different mazes as well as play w/o maze are poss ible.
Date : 2025-12-29 Size : 5kb User : 阳关
[matlab] weightpercent DL : 0: Returns weighted percentiles of a sample given the weight vector w ％ The idea is to give more emphasis in some examples of data as compared to ％ others by giving more weight. For example, we could give lower weights to ％ the outliers. ％ The motivation to write this function is to compute percentiles for Monte ％ Carlos simulations where some simulations are very bad (in terms of goodness ％ of fit between simulated and actual value) than the others and to give ％ the lower weights based on some goodness of fit criteria.-Returns weighted percentiles of a sample given the weight vector w The idea is to give more emphasis in some examples of data as compared to others by giving more weight. For example, we could give lower weights to the outliers. The motivation to write this function is to compute percentiles for Monte Carlos simulations where some simulations are very bad (in terms of goodness of fit between simulated and actual value) than the others and to give the lower weights based on some goodness of fit criteria .
Date : 2025-12-29 Size : 2kb User : Jack
[matlab] cst DL : 0: H.S.Park, D-S.Kim, and W.H.Kwon "A Scheduling Method for Network-based Control Systems", IEEE Transaction on Control System Technology, Vol.10, No.3, pp. 318-330, May, 2002 (Simulation Example 1- Matlab Code) -HSPark, DS.Kim, and WHKwon A Scheduling Method for Network-based Control Systems , IEEE Transaction on Control System Technology, Vol.10, No.3, pp. 318-330, May, 2002 (Simulation Example 1- Matlab Code)
Date : 2025-12-29 Size : 3kb User : 田之秋
[matlab] NLMS DL : 0: 若不希望用与估计输入信号矢量有关的相关矩阵来加快LMS算法的收敛速度，那么可用变步长方法来缩短其自适应收敛过程，其中一个主要的方法是归一化LMS算法（NLMS算法），变步长的更新公式可写成 W（n+1）=w（n）+ e（n）x（n） =w（n）+ （3.1）式中， = e（n）x（n）表示滤波权矢量迭代更新的调整量。为了达到快速收敛的目的，必须合适的选择变步长的值，一个可能策略是尽可能多地减少瞬时平方误差，即用瞬时平方误差作为均方误差的MSE简单估计，这也是LMS算法的基本思想。 -Want to estimate if the input signal vector and the relevant matrix to speed up the convergence rate of LMS algorithm, then the variable step size method can be used to shorten its adaptive convergence process, one of the main method is normalized LMS algorithm (NLMS algorithm) , variable step-size update formula can be written W (n+ 1) = w (n)+ e (n) x (n) = w (n)+ (3.1) where, = e (n) x (n) the right to express filter update vector iterative adjust the volume. In order to achieve the purpose of fast convergence, we must choose the appropriate value of variable step size, a possible strategy is as much as possible to reduce the instantaneous squared error, which uses the instantaneous squared error as the mean square error MSE of the simple estimate, which is the basic LMS algorithm思想.
Date : 2025-12-29 Size : 3kb User : 闫丰
[matlab] melcepst DL : 0: 计算Mel倒谱系数的matlab程序： MELCEPST Calculate the mel cepstrum of a signal C=(S,FS,W,NC,P,N,INC,FL,FH) 使用: c=melcepst(s,fs) ％ calculate mel cepstrum with 12 coefs, 256 sample frames-Mel cepstrum coefficients calculated the matlab procedure: MELCEPST Calculate the mel cepstrum of a signal C = (S, FS, W, NC, P, N, INC, FL, FH) using: c = melcepst (s, fs) calculate mel cepstrum with 12 coefs, 256 sample frames
Date : 2025-12-29 Size : 2kb User : 凝空子
[matlab] FiberGratingSpectra DL : 1: 传输矩阵法计算啁啾光栅反射谱本节中给出传输矩阵法计算啁啾光栅反射谱和时延的完整M at lab 程序实例, 本段代码在 M at lab513 和W indow s2000 环境中运行通过。运行结果如图8 所示。可以改变光栅长度、有效折射率、折射率调制深度、啁啾系数等参数来获得不同参数下光栅反射谱和时延曲线。如果打开“％切趾”行的屏蔽符“％ ”则可得到切趾后光栅反射谱和时延特性曲线, 此时计算所得的曲线将比图8 中所示的曲线平滑很多。-Transfer matrix method to calculate reflection spectrum of chirped grating is given in this section transfer matrix method to calculate chirped grating reflection spectrum and the delay of a complete example of M at lab procedures, the above code in M at lab513 and W indow s2000 environment to run through. The results shown in Figure 8. Can change the grating length, the effective refractive index, refractive index modulation depth and chirp coefficient parameters to obtain different parameters of grating reflection spectrum and the time delay curve. If you open Apodization line shielding Fu can be grating after apodization reflection spectrum and the delay characteristic curve, the curve at this time will be calculated as shown in Figure 8 a lot of curve smoothing.
Date : 2025-12-29 Size : 1kb User : 金沧
[matlab] a DL : 0: 基于非负矩阵分解（NMF）的人脸特征提取算法，NMF基本思想是找到一个线性子空间W，使的构成子空间的基本图像的像素点都是正值，而且人脸图像在子空间上的投影系数也是正数-Non-negative Matrix Factorization (NMF) of facial feature extraction algorithm, NMF basic idea is to find a linear sub-space W, so that the composition of sub-space of the basic image pixels are positive, and face image in the sub-space projection coefficient is positive
Date : 2025-12-29 Size : 2kb User : xuying
[matlab] beibaowenti DL : 0: 有N件物品和一个容量为V的背包。第i件物品的费用是c，价值是w。求解将哪些物品装入背包可使这些物品的费用总和不超过背包容量，且价值总和最大。-There are N items and a knapsack capacity of V' s. No. i is the cost of items c, the value of w. Solving items into the backpack which will enable the cost of these items does not exceed the sum of the capacity of backpack, and the sum of the maximum value.
Date : 2025-12-29 Size : 1kb User : gaozi1012
[matlab] EUCLIDEAN_Algorithm DL : 0: Euclidean节点定位是由美国路特葛斯大学利用距离矢量路由和GPS定位原理提供出一种分布式自主定位算法-Node localization Euclidean path by the Rutgers Universitys use of distance vector routing and GPS positioning to provide a principle of self-positioning algorithm for distributed
Date : 2025-12-29 Size : 1.01mb User : qinhua
[matlab] fit_maxwell_pdf DL : 0: fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples. fits data to the probability of the form: p(r) = sqrt(2/pi)*(a^(-3/2))*(r^2)*exp(-(r^2)/(2*a)) with parameter: a format: result = fit_maxwell_pdf( x,y,W,hAx ) input: y - vector, samples of the histogram to be fitted x - vector, position of the samples of the histogram (i.e. y = f(x,a)) W - matrix or scalar, a square weighting matrix of the size NxN where N = length(y), or 0 to indicate no weighting is needed. hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields a - fitted parameter VAR - variance of the estimation type- weighted LS or not weighted LS iter- number of iteration for the solution- fit_maxwell_pdf - Non Linear Least Squares fit of the maxwellian distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples. fits data to the probability of the form: p(r) = sqrt(2/pi)*(a^(-3/2))*(r^2)*exp(-(r^2)/(2*a)) with parameter: a format: result = fit_maxwell_pdf( x,y,W,hAx ) input: y - vector, samples of the histogram to be fitted x - vector, position of the samples of the histogram (i.e. y = f(x,a)) W - matrix or scalar, a square weighting matrix of the size NxN where N = length(y), or 0 to indicate no weighting is needed. hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields a - fitted parameter VAR - variance of the estimation type- weighted LS or not weighted LS iter- number of iteration for the solution
Date : 2025-12-29 Size : 2kb User : resident e
[matlab] fit_rayleigh_pdf DL : 0: fit_rayleigh_pdf - Non Linear Least Squares fit of the Rayleigh distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples.fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s with parameter: s format:result = fit_rayleigh_pdf( x,y,W,hAx ) input: y - vector, samples of the histogram to be fitted x - vector, position of the samples of the histogram (i.e. y = f(x,a)) W - matrix or scalar, a square weighting matrix of the size NxN where N = length(y), or 0 to indicate no weighting is needed. hAx - handle of an axis, on which the fitted distribution is plotted output: result - structure with the fields s - fitted parameter VAR - variance of the estimation type- weighted LS or not weighted LS iter- number of iteration for the solution-fit_rayleigh_pdf - Non Linear Least Squares fit of the Rayleigh distribution. given the samples of the histogram of the samples, finds the distribution parameter that fits the histogram samples.fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s with parameter: s format:result = fit_rayleigh_pdf( x,y,W,hAx ) input: y - vector, samples of the histogram to be fitted x - vector, position of the samples of the histogram (i.e. y = f(x,a)) W - matrix or scalar, a square weighting matrix of the size NxN where N = length(y), or 0 to indicate no weighting is needed. hAx - handle of an axis, on which the fitted distribution is plotted output: result - structure with the fields s - fitted parameter VAR - variance of the estimation type- weighted LS or not weighted LS iter- number of iteration for the solution
Date : 2025-12-29 Size : 2kb User : resident e
[matlab] computedftmatrix DL : 0: compute dft matrix, creates a W matrix of size N
Date : 2025-12-29 Size : 1kb User : carloskoreano
[matlab] w DL : 0: 这段程序用于实现封闭空间逃生模拟，通过这段程序可以看到在一个封闭空间中，很多人是如何高效逃生的。-This program used to implement analog to escape an enclosed space, you can see through this process in a closed space, a lot of people how to effectively escape.
Date : 2025-12-29 Size : 8kb User : 雷晓义
[matlab] ww DL : 0: 判断矩阵A，计算A 的各列归一化向量及“和积法”求得的排序向量w 求出诱导矩阵C，找出使|Cij-1|达到最大值的ij记为k , l 若Ckl> 1, 则若Akl为整数, 令A′k l= Akl- 1。GCI是此函数完成矩阵A的GCI的计算-Judgment matrix A, the ranking vector A w calculated the normalized vector and "product" for induction of matrix C, find the maximum |Cij-1| ij for K, l if Ckl> is 1, if Akl is an integer, the A k l= Akl- 1. GCI is to compute this function matrix A GCI
Date : 2025-12-29 Size : 1kb User : 吴魏
[matlab] DTFT DL : 0: 给出了x(n)=A*a^n*cos(w*n+theta),A，a，w，theta均为实数，程序中给出了如何不同过matlab的自带工具箱求解其DTFT的过程-Given x (n) = A* a ^ n* cos (w* n+ theta), A, a, w, theta, are real numbers, the procedure given how different matlab comes toolbox for solving itsthe process of DTFT
Date : 2025-12-29 Size : 13kb User : shujian
[matlab] Choosing-Coins-To-Match-a-Given-Value DL : 0: The change making problem is given a target value C and a set of N coin denominations with value W. The task is to determine the minimum number of coins needed to form the given value. In the unbounded change making problem, there are a limitless supply of coins of each denomination. In the bounded change making problem, each denomination is available only up to some given limit. For some sets of denominations, there will be target values that cannot be formed. (This relates to Frobenius s problem.)
Date : 2025-12-29 Size : 1kb User : Yu Deyang
[matlab] pin DL : 0: PIN photodiode. inputs x: optical signal fs: sampling frequency (Hz) Resp: receiver respsonsivity (A/W) R: receiver resistance (Ohm) T: temperature (degrees K) Id: dark current(A) output xrec: electrical signal - PIN photodiode. inputs x: optical signal fs: sampling frequency (Hz) Resp: receiver respsonsivity (A/W) R: receiver resistance (Ohm) T: temperature (degrees K) Id: dark current(A) output xrec: electrical signal
Date : 2025-12-29 Size : 1kb User : karnesi
[matlab] V-W-A DL : 0: 用解析法对时间取一次二次导数，并写成矩阵形式，既可得到速度和加速度方程式- 36/5000 With the analytic method to take a second derivative of time, and write the matrix form, can get the speed and acceleration equations
Date : 2025-12-29 Size : 1kb User : 王博文
[matlab] H.W DL : 0: this file is a estimation matlab code for mont carlo
Date : 2025-12-29 Size : 104kb User : soley

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