代码搜索：Sampling

找到约 3,969 项符合「Sampling」的源代码

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m adsgn.m

function [B,A] = adsgn(Fs); % ADSGN Design of a A-weighting filter. % [B,A] = ADSGN(Fs) designs a digital A-weighting filter for % sampling frequency Fs. Usage: Y = FILTER(B,A,X). % Warni
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m cdsgn.m

function [B,A] = cdsgn(Fs); % CDSGN Design of a A-weighting filter. % [B,A] = CDSGN(Fs) designs a digital A-weighting filter for % sampling frequency Fs. Usage: Y = FILTER(B,A,X). % Warni
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m ip_07_01.m

% MATLAB script for Illustrated Problem 7.1. echo on T=1; delta_T=T/200; % sampling interval alpha=0.5; % rolloff factor fc=40/T; % carrier frequency A_m=1;
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m ip_06_03.m

% MATLAB script for Illustrative Problem 6.3. echo on f_cutoff=2000; % the desired cutoff frequency f_stopband=2500; % the actual stopband frequency fs=10000; % the sampling frequency f1=
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m fashe.m

function fasheji Pow = -30; % Average transmitted power (dBm) fc = 50e9; % sampling frequency numbits = 8; % number of bits generated by the source Ts =30e-9; Nh = 15;
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m fashejiboxing.m

function asdas Pow = -30; % Average transmitted power (dBm) fc = 50e9; % sampling frequency numbits = 4; % number of bits generated by the source Ts =5e-9; % frame time
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m fidelity_error.m

function fidelity_error(freq,Ny_multiple); % fidelity_error(freq,Ny_multiple); % % This script demonstrates how sampling faster than the Nyquist % frequency forces amplitude modulation for all sample
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m hmc.m

function [samples, energies, diagn] = hmc(f, x, options, gradf, varargin) %HMC Hybrid Monte Carlo sampling. % % Description % SAMPLES = HMC(F, X, OPTIONS, GRADF) uses a hybrid Monte Carlo % algorithm
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www.eeworm.com/read/177674/9442593

m demmet1.m

function demmet1(plot_wait) %DEMMET1 Demonstrate Markov Chain Monte Carlo sampling on a Gaussian. % % Description % The problem consists of generating data from a Gaussian in two % dimensions using a
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m hmc.m

function [samples, energies, diagn] = hmc(f, x, options, gradf, varargin) %HMC Hybrid Monte Carlo sampling. % % Description % SAMPLES = HMC(F, X, OPTIONS, GRADF) uses a hybrid Monte Carlo % algorithm
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