智慧屏安装APP的最佳实践与跨平台小程序开发的结合
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2022-12-02
rands函数的用法
有如下程序,
clc;clear;[a,b]=rands(5,1);ab[c,d]=rands(1,5);cd
输出如下:
a = -0.5749 0.6785 0.2576 -0.7325 -0.5857 b = 0.2144 0.2598 -0.2590 0.1503 -0.0972 c = -0.9122 -0.9456 -0.3746 -0.9743 -0.2321 d = 0.3662
有关rands函数说明如下:
rands Symmetric random weight/bias initialization function Syntax W = rands(S,PR) M = rands(S,R) v = rands(S); Description rands is a weight/bias initialization function. rands(S,PR) takes, S -- Number of neurons PR -- R x 2 matrix of R input ranges and returns an S-by-R weight matrix of random values between -1 and 1. rands(S,R) returns an S-by-R matrix of random values. rands(S) returns an S-by-1 vector of random values. Examples Here three sets of random values are generated with rands. rands(4,[0 1; -2 2]) rands(4) rands(2,3) Network Use To prepare the weights and the bias of layer i of a custom network to be initialized with rands Set net.initFcn to 'initlay'. (net.initParam will automatically become initlay's default parameters.) Set net.layers{i}.initFcn to 'initwb'. Set each net.inputWeights{i,j}.initFcn to 'rands'. Set each net.layerWeights{i,j}.initFcn to 'rands'. Set each net.biases{i}.initFcn to 'rands'. To initialize the network call init
没有说明,如何出现上述结果,百度之:
function [w,b] = rands(s,pr)%RANDS Symmetric random weight/bias initialization function.%% Syntax%% W = rands(S,PR)% M = rands(S,R)% v = rands(S);%% Description%% RANDS is a weight/bias initialization function.%% RANDS(S,PR) takes,% S - number of neurons.% PR - Rx2 matrix of R input ranges.% and returns an S-by-R weight matrix of random values between -1 and 1.%% RANDS(S,R) returns an S-by-R matrix of random values.% RANDS(S) returns an S-by-1 vector of random values.%% Examples%% Here three sets of random values are generated with RANDS.%% rands(4,[0 1; -2 2])% rands(4)% rands(2,3)%% Network Use%% To prepare the weights and the bias of layer i of a custom network% to be initialized with RANDS:% 1) Set NET.initFcn to 'initlay'.% (NET.initParam will automatically become INITLAY's default parameters.)% 2) Set NET.layers{i}.initFcn to 'initwb'.% 3) Set each NET.inputWeights{i,j}.initFcn to 'rands'.% Set each NET.layerWeights{i,j}.initFcn to 'rands';% Set each NET.biases{i}.initFcn to 'rands'.%% To initialize the network call INIT.%% See also RANDNR, RANDNC, INITWB, INITLAY, INIT% Mark Beale, 1-31-92% Revised 12-15-93, MB% Revised 11-31-97, MB% Copyright 1992-2008 The MathWorks, Inc.% $Revision: 1.1.6.7 $ $Date: 2008/06/20 08:04:33 $fn = mfilename;if (nargin < 1), error('NNET:Arguments','Not enough arguments.'); endif ischar(s) switch(s) case 'name' w = 'Midpoint'; otherwise, error('NNET:Arguments',['Unrecognized code: ''' s '''']) end returnendif nargin == 1 r = 1;elseif size(pr,2) == 1 r = pr;else r = size(pr,1);endw = 2*rand(s,r)-1;//注意% **[ NNT2 Support ]**if nargout == 2 b = 2*rand(s,1)-1; //注意
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