代码搜索：ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
代码结果 3,786
www.eeworm.com/read/220289/14843706
m demje2.m
% DEMJE2 Demonstrate nonlinear time series joint estimation for Mackey-Glass chaotic time series
%
% The Mackey-Glass time-delay differential equation is defined by
%
% dx(t)/dt = 0.2x
www.eeworm.com/read/220289/14843712
m demse1.m
% DEMSE1 Demonstrate state estimation on a simple 2nd order LTI system.
%
% This is a simple demonstration of how to use the ReBEL toolkit for state estimation on
% a simple 2nd order LTI syst
www.eeworm.com/read/220289/14843714
m demse3.m
% DEMSE3 Demonstrate nonlinear time series state estimation for Mackey-Glass chaotic time series
%
% The Mackey-Glass time-delay differential equation is defined by
%
% dx(t)/dt = 0.2x(t-
www.eeworm.com/read/218840/14904402
m d_order.m
%D_ORDER HOSA Demo: Linear Processes - ARMA model order determination.
echo off
% Demo of arorder, maorder
% A. Swami Jan 20, 1995
% Copyright (c) 1991-2001 by United Signals & Systems, Inc
www.eeworm.com/read/215497/15059502
m program_10_1.m
% Program 10_1
% Estimation of FIR Filter Order Using remezord
%
fedge = input('Type in the bandedges = ');
mval = input('Desired magnitude values in each band = ');
dev = input('Allowable deviat
www.eeworm.com/read/215497/15059692
m program_10_1.m
% Program 10_1
% Estimation of FIR Filter Order Using remezord
%
fedge = input('Type in the bandedges = ');
mval = input('Desired magnitude values in each band = ');
dev = input('Allowable deviat
www.eeworm.com/read/294248/8244962
m matlab_wan_ldpc.m
function wman1()
clear all;
fprintf('Start! Please waiting ...\n');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Parameters for system configura
www.eeworm.com/read/293183/8310578
m parzenml.m
%PARZENML Optimum smoothing parameter in Parzen density estimation.
%
% h = parzenml(A)
%
% Maximum likelihood estimation for the smoothing parameter in the
% Parzen denstity estimation of the dat
www.eeworm.com/read/370043/9621766
m bartlettse.m
function phi = bartlettse(y,M,L)
%
% The Bartlett method of spectra estimation.
%
% phi=bartlettse(y,M,L);
%
% y -> the data vector
% M -> the length of subsequences of y
% L ->
www.eeworm.com/read/370043/9621769
m bartlettse.m
function phi = bartlettse(y,M,L)
%
% The Bartlett method of spectra estimation.
%
% phi=bartlettse(y,M,L);
%
% y -> the data vector
% M -> the length of subsequences of y
% L ->