代码搜索：Sampling

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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 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 prog7b4a.m

% % Program name - prog7b4a.m % m-file for calculating the optimal FIR filter coefficients % and plotting frequency response for Example 7B.4 % Fs=50000; % Sampling frequency %
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m prog7b4a.m

% % Program name - prog7b4a.m % m-file for calculating the optimal FIR filter coefficients % and plotting frequency response for Example 7B.4 % Fs=50000; % Sampling frequency %
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m bft_create_filter1.m

%BFT_CREATE_FILTER1 Create linear phase low pass filter. Method #1 % This function creates a low pass filter, with a cutting frequency % at half the sampling frequency. The design method is base
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m gaussfilt.m

% GAUSSFILT Design a Gaussian Low-Pass Filter % % [B, A] = GAUSSFILT(BW, N) % BW is the 3-dB bandwidth with 1.0 being 1/2 the % sampling frequency. N is the number of taps. % % function
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m# #demmet1.m#

function samples=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 % dimens
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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 acquisition.m

function [amp,ccn,cfrq]=Acquisition(lpfdata, svnum) % **************initial parameters**************** fs=4.8e+6; % the sampling frq; ts=1/fs; fc=30e+3; % the center frq without the Doppl
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