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【手写数字识别】基于RBM神经网络手写数字识别含Matlab源码

来源：互联网收集：自由互联发布时间：2022-06-18

1 简介【手写数字识别】基于RBM神经网络手写数字识别含Matlab源码 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

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 EDIT
gui_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});
end
if 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_gui2
handles.output = hObject;
% Update handles structure
guidata(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 structure
varargout{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)*100
batch_index = randint(1,1,[1,100]);%产生随机批次号，1-100
image_index = randint(1,1,[1,100]);%产生该批图像中的随机测试图像号，1-100
data = 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);