【图像识别】基于Hopfield神经网络实现字母识别matlab代码-北京尧图网络

1 简介基于离散Hopfield神经网络理论,对带噪声的字母识别进行研究.根据神经网络的联想记忆功能,在考虑实际情况的条件下进行模型建立,通过MATLAB软件进行函数创建与设计实现,并对结果进行分析,同时提出应用扩展.离散神经网络是一种单层、输出为二值的反馈型的网络。假设有一个由五个神经元组成的离散 Ho pfield 神经网络,其结构如图 1 所示。2 部分代码function varargout hopfieldNetwork(varargin) % HOPFIELDNETWORK M-file for hopfieldNetwork.fig % HOPFIELDNETWORK, by itself, creates a new HOPFIELDNETWORK or raises the existing % singleton*. % % H HOPFIELDNETWORK returns the handle to a new HOPFIELDNETWORK or the handle to % the existing singleton*. % % HOPFIELDNETWORK(CALLBACK,hObject,eventData,handles,...) calls the local % function named CALLBACK in HOPFIELDNETWORK.M with the given input arguments. % % HOPFIELDNETWORK(Property,Value,...) creates a new HOPFIELDNETWORK or raises the % existing singleton*. Starting from the left, property value pairs are % applied to the GUI before hopfieldNetwork_OpeningFunction gets called. An % unrecognized property name or invalid value makes property application % stop. All inputs are passed to hopfieldNetwork_OpeningFcn via varargin. % % *See GUI Options on GUIDEs Tools menu. Choose GUI allows only one % instance to run (singleton). % % See also: GUIDE, GUIDATA, GUIHANDLES % Copyright 2002-2003 The MathWorks, Inc. % Edit the above text to modify the response to help hopfieldNetwork % Last Modified by GUIDE v2.5 21-Jan-2007 15:45:38 % Begin initialization code - DO NOT EDIT gui_Singleton 1; gui_State struct(gui_Name, mfilename, ... gui_Singleton, gui_Singleton, ... gui_OpeningFcn, hopfieldNetwork_OpeningFcn, ... gui_OutputFcn, hopfieldNetwork_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 hopfieldNetwork is made visible. function hopfieldNetwork_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 hopfieldNetwork (see VARARGIN) % Choose default command line output for hopfieldNetwork handles.output hObject; N str2num(get(handles.imageSize,string)); handles.W []; handles.hPatternsDisplay []; % Update handles structure guidata(hObject, handles); % UIWAIT makes hopfieldNetwork wait for user response (see UIRESUME) % uiwait(handles.figure1); % --- Outputs from this function are returned to the command line. function varargout hopfieldNetwork_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; % --- Executes on button press in reset. function reset_Callback(hObject, eventdata, handles) % cleans all data and enables the change of the number of neurons used for n1 : length(handles.hPatternsDisplay) delete(handles.hPatternsDisplay(n)); end handles.hPatternsDisplay []; set(handles.imageSize,enable,on); handles.W []; guidata(hObject, handles); function imageSize_Callback(hObject, eventdata, handles) % hObject handle to imageSize (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) num get(hObject,string); n str2num(num); if isempty(n) num 32; set(hObject,string,num); end if n 32 warndlg(It is strongly recomended NOT to work with networks with more then 32^2 neurons!,!! Warning !!) end % --- Executes during object creation, after setting all properties. function imageSize_CreateFcn(hObject, eventdata, handles) % hObject handle to imageSize (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 set(hObject,BackgroundColor,white); else set(hObject,BackgroundColor,get(0,defaultUicontrolBackgroundColor)); end % --- Executes on button press in loadIm. function loadIm_Callback(hObject, eventdata, handles) [fName dirName] uigetfile(*.bmp;*.tif;*.jpg;*.tiff); if fName set(handles.imageSize,enable,off); cd(dirName); im imread(fName); N str2num(get(handles.imageSize,string)); im fixImage(im,N); imagesc(im,Parent,handles.neurons); colormap(gray); end % hObject handle to run (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) function im fixImage(im,N) % if isrgb(im) if length( size(im) ) 3 im rgb2gray(im); end im double(im); m min(im(:)); M max(im(:)); im (im-m)/(M-m); %normelizing the image im imresize(im,[N N],bilinear); %im (im 0.5)*2-1; %changing image values to -1 1 im (im 0.5); %changing image values to 0 1 % --- Executes on slider movement. function noiseAmount_Callback(hObject, eventdata, handles) % hObject handle to noiseAmount (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) percent get(hObject,value); percent round(percent*100); set(handles.noisePercent,string,num2str(percent)); % Hints: get(hObject,Value) returns position of slider % get(hObject,Min) and get(hObject,Max) to determine range of slider % --- Executes during object creation, after setting all properties. function noiseAmount_CreateFcn(hObject, eventdata, handles) % hObject handle to noiseAmount (see GCBO) % eventdata reserved - to be defined in a future version of MATLAB % handles empty - handles not created until after all CreateFcns called % Hint: slider controls usually have a light gray background, change % usewhitebg to 0 to use default. See ISPC and COMPUTER. usewhitebg 1; if usewhitebg set(hObject,BackgroundColor,[.9 .9 .9]); else set(hObject,BackgroundColor,get(0,defaultUicontrolBackgroundColor)); end3 仿真结果4 参考文献[1]殷璇, 王生. 基于离散Hopfield神经网络的字母识别研究[J]. 计算机与数字工程, 2011, 39(1):4.**部分理论引用网络文献若有侵权联系博主删除。**

【图像识别】基于Hopfield神经网络实现字母识别matlab代码

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