欢迎来到海神之光博客之家✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab信号处理仿真内容点击①Matlab信号处理 进阶版②付费专栏Matlab信号处理初级版⛳️关注CSDN海神之光更多资源等你来⛄一、隐马尔可夫模型简介隐马尔可夫模型(Hidden Markov model, HMM)是一种结构最简单的动态贝叶斯网的生成模型它也是一种著名的有向图模型。它是典型的自然语言中处理标注问题的统计机器学模型本文将重点介绍这种经典的机器学习模型。1 引言假设有三个不同的骰子(6面、4面、8面)每次先从三个骰子里面选择一个每个骰子选中的概率为1/3如下图所示重复上述过程得到一串数值[1,6,3,5,2,7]。这些可观测变量组成可观测状态链。同时在隐马尔可夫模型中还有一条由隐变量组成的隐含状态链在本例中即骰子的序列。比如得到这串数字骰子的序列可能为[D6, D8, D8, D6, D4, D8]。隐马尔可夫型示意图如下所示图中箭头表示变量之间的依赖关系。图中各箭头的说明如下在任意时刻观测变量(骰子)仅依赖于状态变量(哪类骰子)同时t时刻的状态qt仅依赖于t-1时刻的状态qt-1。这就是马尔科夫链即系统的下一时刻仅由当前状态无记忆即“齐次马尔可夫性假设”2 隐马尔可夫模型的定义根据上面的例子这里给出隐马尔可夫的定义。隐马尔科夫模型是关于时序的概率模型描述由一个隐藏的马尔可夫链随机生成不可观测的状态随机序列再由各个状态生成一个可观测的随机序列的过程隐藏的马尔可夫链随机生成的状态序列称为状态序列(也就上面例子中的D6D8等)每个状态生成一个观测而由此产生的观测随机序列称为观测序列(也就上面例子中的16等)。序列的每个位置又可以看作是一个时刻。隐马尔可夫模型由初始的概率分布、状态转移概率分布以及观测概率分布确定。具体的形式如下这里设Q是所有可能的状态的集合V是所有可能的观测的集合即有3 前向算法对于步骤一的初始是初始时刻的状态i1 q1和观测o1的联合概率。步骤(2) 是前向概率的递推公式计算到时刻t1部分观测序列为o1,o2,…,ot,ot1 且在时刻t1处于状态qi的前向概率。如上图所示既然at(j)是得到时刻t观测到o1,o2,…,ot并在时刻t处于状态的qj前向概率那么at(j)aji就是到时刻t观测到o1,o2,…,ot并在是时刻t处于qj状态而在时刻t1到达qi状态的联合概率。对于这个乘积在时刻t的所有可能的N个状态求和其结果就是到时刻t观测为o1,o2,…,ot并在时刻t1处于状态qi的联合概率。最后第三步计算出P(O|lamda)的结果。当然这里只是介绍了诸多算法中的一种类似的还有后向算法(大家可以看相关的书籍进行了解)。对于动态规划的解决隐马尔科夫模型预测问题应用最多的是维特比算法。⛄二、部分源代码function varargout SleepStatus(varargin)% SLEEPSTATUS MATLAB code for SleepStatus.fig% SLEEPSTATUS, by itself, creates a new SLEEPSTATUS or raises the existing% singleton*.%% H SLEEPSTATUS returns the handle to a new SLEEPSTATUS or the handle to% the existing singleton*.%% SLEEPSTATUS(‘CALLBACK’,hObject,eventData,handles,…) calls the local% function named CALLBACK in SLEEPSTATUS.M with the given input arguments.%% SLEEPSTATUS(‘Property’,‘Value’,…) creates a new SLEEPSTATUS or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before SleepStatus_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to SleepStatus_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 SleepStatus% Last Modified by GUIDE v2.5 21-Oct-2020 17:16:55% Begin initialization code - DO NOT EDITgui_Singleton 1;gui_State struct(‘gui_Name’, mfilename, …‘gui_Singleton’, gui_Singleton, …‘gui_OpeningFcn’, SleepStatus_OpeningFcn, …‘gui_OutputFcn’, SleepStatus_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{:});elsegui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% — Executes just before SleepStatus is made visible.function SleepStatus_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 SleepStatus (see VARARGIN)% Choose default command line output for SleepStatushandles.output hObject;set(handles.text2,‘string’,‘Sleep status detector’,‘foregroundcolor’,‘b’,‘fontsize’,20);set(handles.pushbutton1,‘String’,‘打开文件’);set(handles.pushbutton2,‘String’,‘播放且判断’);set(handles.pushbutton3,‘String’,‘停止’);set(handles.edit1,‘String’,‘实时判断结果’);set(handles.edit2,‘String’,‘过往判断结果’);set(handles.edit2,‘Max’,10);set(handles.edit2,‘Min’,0);cla(handles.axes1);cla(handles.axes2);global player timer_counter accurate_time n_last n_last1 all_result numplayer[];timer_counter 0;accurate_time 0;n_last 2;n_last1 2;num 1;all_result{};% Update handles structureguidata(hObject, handles);% UIWAIT makes SleepStatus wait for user response (see UIRESUME)% uiwait(handles.figure1);% — Outputs from this function are returned to the command line.function varargout SleepStatus_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;% — Executes on button press in pushbutton1.function pushbutton1_Callback(hObject, eventdata, handles)% hObject handle to pushbutton1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)global wavfilename timer_counter all_result num[FileName,PathName] uigetfile(‘*.wav’,‘Select the wav-file’);if FileName0wavfilename [];returnendwavfilename [PathName,FileName];[x,fs] audioread(wavfilename);x mean(x,2);axes(handles.axes1);plot(x);ylim([-1 1]);timer_counter 0;accurate_time 0;all_result{};set(handles.edit2,‘string’,‘’);num 1;% — Executes on button press in pushbutton2.function pushbutton2_Callback(hObject, eventdata, handles)% hObject handle to pushbutton2 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)global wavfilename tAxis player myStruct start_minute start_secondsif isempty(wavfilename)returnend%defaultdurT 3060; %secondsfs 32000;durS fsdurT; %samples[x,fs] audioread(wavfilename);x mean(x,2);durT size(x,1)/fs;durS size(x,1);dt 1/fs;tAxis dt:dt:durT;frameRate 25; %fpsframeT 1/frameRate;mag 1;axes(handles.axes1);cla(handles.axes1);plot(tAxis, x);ylim([-mag mag])xlim([0 durT])xlabel(‘Time [s]’)playHeadLoc 0;% hold on;ax plot([0 playHeadLoc], [-mag mag], ‘r’, ‘LineWidth’, 2);player audioplayer(x, fs);myStruct.playHeadLoc playHeadLoc;myStruct.frameT frameT;myStruct.ax1 handles.axes1;myStruct.ax2 handles.axes2;myStruct.edit1 handles.edit1;myStruct.edit2 handles.edit2;tmr1 timer(‘ExecutionMode’, ‘FixedRate’, …‘Period’, 0.5, …‘TimerFcn’, {timerCallback});% tmr2 timer(‘ExecutionMode’, ‘FixedRate’, …% ‘Period’, 0.1, …% ‘TimerFcn’, {timerCallback2});handles.timer1 tmr1;% handles.timer2 tmr2;guidata(hObject, handles);start_time clock();start_seconds start_time(6);start_minute start_time(5);start(tmr1);% start(tmr2);playblocking(player);% play(player);if ~isplaying(player)stop(handles.timer1);% stop(handles.timer2);end% function timerCallback2(hObj, eventdata)% global accurate_time% accurate_time accurate_time 0.1;function timerCallback(hObj, eventdata)global wavfilename myStruct tAxis timer_counter accurate_time start_minute start_seconds n_last n_last1 all_result num[x1,fs] audioread(wavfilename);x1 mean(x1,2);length_max length(x1);% timer_counter accurate_time;start_time clock();seconds start_time(6);minute start_time(5);timer_counter (minute60seconds)-(start_minute60start_seconds);% disp(timer_counter)axes(myStruct.ax1);plot(tAxis,x1);line([timer_counter timer_counter],[-1 1],‘color’,‘r’);axis([tAxis(1) tAxis(end) -1 1]);time1 timer_counter;time2 time1 1;%1sidx1 fix(fstime1);idx2 fix(fstime2);if (idx11)idx1 1;endif(idx1length_max)idx1 length_max;endif(idx2length_max)idx2 length_max;endif(idx1idx2)returnendx1 x1([idx1:idx2]);axes(myStruct.ax2);plot(x1,‘color’,[1, 0.6732, 0]);axis([1 1*fs1 -.5 .5]);%判断结果load hmm.mataddpath (genpath(‘HMMall’),‘-end’);warning(‘off’);class_folder{‘NormalBreathe’,‘FastBreathe’,‘Snore’};ResultStr class_folder;k x1;datacell MFCC(k,fs);% size(datacell)datacell datacell’;for j1:size(hmm,2)HMM hmm{j};loglik(j) mhmm_logprob(datacell,HMM.prior, HMM.transmat, HMM.mu, HMM.Sigma, HMM.mixmat);%计算概率end[d,n] max(loglik);% fprintf(‘文件名:%s识别结果:%s\n’, [class_folder{i},‘\’,fname],char(ResultStr{n}));n_judge n_last1;%延迟1秒if n_judge1set(myStruct.edit1,‘string’,[num2str(time1),’ s: ‘,char(ResultStr{n_judge})]);set(myStruct.edit1,‘string’,[num2str(time1),’ s: ,char(ResultStr{n_judge})]);set(myStruct.edit1,‘foregroundcolor’,‘r’);set(myStruct.edit1,‘fontsize’,20);all_result{num} num2str(time1);num num1;set(myStruct.edit2,‘string’,all_result);set(myStruct.edit2,‘foregroundcolor’,‘r’);elseif(n_judge2)set(myStruct.edit1,‘string’,[num2str(time1),’ s: ‘,char(ResultStr{n_judge})]);set(myStruct.edit1,‘foregroundcolor’,‘g’);set(myStruct.edit1,‘fontsize’,20);elseset(myStruct.edit1,‘string’,[num2str(time1),’ s: ,char(ResultStr{n_judge})]);set(myStruct.edit1,‘foregroundcolor’,‘b’);set(myStruct.edit1,‘fontsize’,20);endn_last1 n_last;n_last n; %结果留着下下次显示rmpath (genpath(‘HMMall’));warning(‘on’);% timer_counter accurate_time;% timer_counter timer_counter 0.5;function edit1_Callback(hObject, eventdata, handles)% hObject handle to edit1 (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 edit1 as text% str2double(get(hObject,‘String’)) returns contents of edit1 as a double% — Executes during object creation, after setting all properties.function edit1_CreateFcn(hObject, eventdata, handles)% hObject handle to edit1 (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 pushbutton3.function pushbutton3_Callback(hObject, eventdata, handles)% hObject handle to pushbutton3 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)global playerif ~isempty(player)stop(player);stop(handles.timer1);% stop(handles.timer2);end% — Executes when user attempts to close figure1.function figure1_CloseRequestFcn(hObject, eventdata, handles)% hObject handle to figure1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Hint: delete(hObject) closes the figuredelete(hObject);global playerif ~isempty(player)stop(player);stop(handles.timer1);% stop(handles.timer2);endfunction edit2_Callback(hObject, eventdata, handles)% hObject handle to edit2 (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 edit2 as text% str2double(get(hObject,‘String’)) returns contents of edit2 as a double% — Executes during object creation, after setting all properties.function edit2_CreateFcn(hObject, eventdata, handles)% hObject handle to edit2 (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⛄三、运行结果⛄四、matlab版本及参考文献1 matlab版本2014a2 参考文献[1]徐洁.基于小波分析的脉搏波信号处理[J].电子设计工程. 2013,21(11)[2]莫玮.小波变换应用于麻醉监测脑电分析研究[J].桂林电子工业学院学报. 1997,(04)3 备注简介此部分摘自互联网仅供参考若侵权联系删除 仿真咨询1 各类智能优化算法改进及应用生产调度、经济调度、装配线调度、充电优化、车间调度、发车优化、水库调度、三维装箱、物流选址、货位优化、公交排班优化、充电桩布局优化、车间布局优化、集装箱船配载优化、水泵组合优化、解医疗资源分配优化、设施布局优化、可视域基站和无人机选址优化2 机器学习和深度学习方面卷积神经网络CNN、LSTM、支持向量机SVM、最小二乘支持向量机LSSVM、极限学习机ELM、核极限学习机KELM、BP、RBF、宽度学习、DBN、RF、RBF、DELM、XGBOOST、TCN实现风电预测、光伏预测、电池寿命预测、辐射源识别、交通流预测、负荷预测、股价预测、PM2.5浓度预测、电池健康状态预测、水体光学参数反演、NLOS信号识别、地铁停车精准预测、变压器故障诊断3 图像处理方面图像识别、图像分割、图像检测、图像隐藏、图像配准、图像拼接、图像融合、图像增强、图像压缩感知4 路径规划方面旅行商问题TSP、车辆路径问题VRP、MVRP、CVRP、VRPTW等、无人机三维路径规划、无人机协同、无人机编队、机器人路径规划、栅格地图路径规划、多式联运运输问题、车辆协同无人机路径规划、天线线性阵列分布优化、车间布局优化5 无人机应用方面无人机路径规划、无人机控制、无人机编队、无人机协同、无人机任务分配6 无线传感器定位及布局方面传感器部署优化、通信协议优化、路由优化、目标定位优化、Dv-Hop定位优化、Leach协议优化、WSN覆盖优化、组播优化、RSSI定位优化7 信号处理方面信号识别、信号加密、信号去噪、信号增强、雷达信号处理、信号水印嵌入提取、肌电信号、脑电信号、信号配时优化8 电力系统方面微电网优化、无功优化、配电网重构、储能配置9 元胞自动机方面交通流 人群疏散 病毒扩散 晶体生长10 雷达方面卡尔曼滤波跟踪、航迹关联、航迹融合