【手写数字识别】基于RBM神经网络手写数字识别含Matlab源码

2022-04-03 11:55 作者:Matlab工程师 0人读过 | 我要投稿

1 简介

2 部分代码

function varargout = core_Test_gui2(varargin)% CORE_TEST_GUI2 MATLAB code for core_Test_gui2.fig% CORE_TEST_GUI2, by itself, creates a new CORE_TEST_GUI2 or raises the existing% singleton*.%% H = CORE_TEST_GUI2 returns the handle to a new CORE_TEST_GUI2 or the handle to% the existing singleton*.%% CORE_TEST_GUI2('CALLBACK',hObject,eventData,handles,...) calls the local% function named CALLBACK in CORE_TEST_GUI2.M with the given input arguments.%% CORE_TEST_GUI2('Property','Value',...) creates a new CORE_TEST_GUI2 or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before core_Test_gui2_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to core_Test_gui2_OpeningFcn via varargin.%% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one% instance to run (singleton)".%% See also: GUIDE, GUIDATA, GUIHANDLES% Edit the above text to modify the response to help core_Test_gui2% Last Modified by GUIDE v2.5 17-Apr-2021 07:50:14% Begin initialization code - DO NOT EDITgui_Singleton = 1;gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @core_Test_gui2_OpeningFcn, ... 'gui_OutputFcn', @core_Test_gui2_OutputFcn, ... 'gui_LayoutFcn', [] , ... 'gui_Callback', []);if nargin && ischar(varargin{1}) gui_State.gui_Callback = str2func(varargin{1});endif nargout [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});else gui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% --- Executes just before core_Test_gui2 is made visible.function core_Test_gui2_OpeningFcn(hObject, eventdata, handles, varargin)% This function has no output args, see OutputFcn.% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% varargin command line arguments to core_Test_gui2 (see VARARGIN)% Choose default command line output for core_Test_gui2handles.output = hObject;% Update handles structureguidata(hObject, handles);% UIWAIT makes core_Test_gui2 wait for user response (see UIRESUME)% uiwait(handles.figure1);% --- Outputs from this function are returned to the command line.function varargout = core_Test_gui2_OutputFcn(hObject, eventdata, handles) % varargout cell array for returning output args (see VARARGOUT);% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Get default command line output from handles structurevarargout{1} = handles.output;function result_Callback(hObject, eventdata, handles)% hObject handle to result (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Hints: get(hObject,'String') returns contents of result as text% str2double(get(hObject,'String')) returns contents of result as a double% --- Executes during object creation, after setting all properties.function result_CreateFcn(hObject, eventdata, handles)% hObject handle to result (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');end% --- Executes on button press in classify.function classify_Callback(hObject, eventdata, handles)% hObject handle to classify (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA) data = handles.data; data_new=[data data]; load linear_classify_weights2;% w1为(2*22*22+1)*256,w_class为(256+1)*10 N=1; %每次只有1幅图像测试 %下面的计算方式通过矩阵拼凑，把偏置的计算也融入矩阵中 dataprobs = [data_new ones(N,1)]; %融入偏置后dataprobs为1*(2*22*22+1) w1probs = (dataprobs*w1)>0; %未融入偏置时w1probs为1*256 w1probs = [w1probs ones(N,1)];%融入偏置后，w1probs为1*(256+1) targetout = exp(w1probs*w_class);%输出层为0*10 %将输出层输出100*10，除以每行的总和以求得归一化比值 targetout = targetout./repmat(sum(targetout,2),1,10); %比较每行中的最大产生10*1的列向量，I每行最大值，J每行最大值序号， %代表识别的数字结果，1-10（分别代表数字0-9） [I J]=max(targetout,[],2); classify_result_str = num2str(J-1);%识别的结果转换为字符串 set(handles.result,'String',classify_result_str); clear data data_new dataprobs w1probs targetout w1 w_class;% --- Executes on button press in select.function select_Callback(hObject, eventdata, handles)% hObject handle to select (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)load testbatchdata;%加载测试图像集，100*(22*22)*100batch_index = randint(1,1,[1,100]);%产生随机批次号，1-100image_index = randint(1,1,[1,100]);%产生该批图像中的随机测试图像号，1-100data = testbatchdata(image_index,:,batch_index);%获取随机的一副测试图像，1*(22*22)clear testbatchdata;image_disp = zeros(22,22);image_disp = reshape(data,22,22);imagesc(image_disp',[0 1]);%显示欲测试图像set(handles.result,'String','');handles.data = data;guidata(hObject,handles);