代码搜索：Probability
找到约 4,670 项符合「Probability」的源代码
代码结果 4,670
www.eeworm.com/read/431621/8664721
m smldpe55.m
function [p]=smldPe55(snr_in_dB)
% [p]=smldPe55(snr_in_dB)
% SMLDPE55 simulates the probability of error for the particular
% value of snr_in_dB, signal-to-noise ratio in dB.
E=1;
SNR=exp(s
www.eeworm.com/read/287843/8665460
m smldpe55.m
function [p]=smldPe55(snr_in_dB)
% [p]=smldPe55(snr_in_dB)
% SMLDPE55 simulates the probability of error for the particular
% value of snr_in_dB, signal-to-noise ratio in dB.
E=1;
SNR=exp(s
www.eeworm.com/read/287843/8665701
m ip_08_07.m
% MATLAB script for Illustrative Problem 8.7
clear
echo on
ep=0.3;
for i=1:2:61
p(i)=0;
for j=(i+1)/2:i
p(i)=p(i)+prod(1:i)/(prod(1:j)*prod(1:(i-j)))*ep^j*(1-ep)^(i-j);
echo off ;
www.eeworm.com/read/386760/8728277
input-rb+bin
Number of Real and Binary Variables (nreal nbinary)
Number of Objectives (2)
Number of Constraints (2)
Population size (100)
Maximum generations (100)
Crossover probability (0.9)
Real-parameter mutati
www.eeworm.com/read/286662/8751805
m hmm_evaluation.m
function P = HMM_evaluation(a, b, V)
% Find the probability of a finite state in a Markov chain
%
% Inputs:
% a - Transition probability matrix
% b - Output generator matrix
% V -
www.eeworm.com/read/386083/8765187
m comp_exam8_3.m
% Bit error probability for DSSS in multi-users
%
N = input('Enter processing gain (chips per bit) ');
K = input('Enter vector of number of users ');
clf
z_dB = 0:.1:30;
z = 10.^(z_dB/10);
LK =
www.eeworm.com/read/284183/8956507
input-rb+bin
Number of Real and Binary Variables (nreal nbinary)
Number of Objectives (2)
Number of Constraints (2)
Population size (100)
Maximum generations (100)
Crossover probability (0.9)
Real-parameter mutati
www.eeworm.com/read/427211/8966051
m hmm_backward.m
function [Lbeta, Lp]=hmm_backword(a, b, pi, o)
%--------------------------------------------------------------------------
%Backword algorithm
%
% [Lbeta,q] = hmm_backword(a,b,pi,o)
%
% inpu
www.eeworm.com/read/283457/9020395
input-rb+bin
Number of Real and Binary Variables (nreal nbinary)
Number of Objectives (2)
Number of Constraints (2)
Population size (100)
Maximum generations (100)
Crossover probability (0.9)
Real-parameter mutati
www.eeworm.com/read/184443/9100248
m ranwalk3d.m
function [rwproc] = ranwalk3d(npoints, p)
% RANWALK3D generate the process (X(n), Y(n), Z(n)),
% where X, Y and Z are random walks which start at 0, jump up
% with probability p and down with p