lq.rar_matlab 语音 信号 加入 噪声_分贝_噪声分贝_语音信号滤波_高斯噪声

fs=22050; f=fs*(0:511)/1024; while 1 K = menu('语音信号数字滤波器','语音采集','加噪声并回放','Butterworth滤波','回放语音','退出程序'); % guide if (K==1) x1=wavread('E:\Matlab滤波器\Windows XP 启动.wav'); %读取语音信号的数据，赋给变量x1 % x1=wavread('E:\Matlab滤波器\recycle.wav'); %读取语音信号的数据，赋给变量x1 % x1=wavread('E:\Matlab滤波器\1.wav'); %读取语音信号的数据，赋给变量x1 % x1=wavread('E:\Matlab滤波器\录音.wav'); %读取语音信号的数据，赋给变量x1 sound(x1,22050); %播放语音信号 F0=fft(x1,1024); %1024点fft变换 figure(1); subplot(2,1,1); plot(x1); %画出滤波后的时域图 title('原始信号的时域'); subplot(2,1,2); plot(f,abs(F0(1:512))); %origion频谱图 title('原始信号的频谱') xlabel('Hz'); ylabel('幅值'); elseif K==2 %加噪声 Y = AWGN(x1,20,0); sound(Y,22050); %播放语音信号 figure(2); subplot(2,1,1); plot(Y);%加噪声高的时域 title('带噪声的时域'); y2=fft(Y,1024); %滤波前fft变换 subplot(2,1,2); plot(f,abs(y2(1:512))); %画出滤波前的频谱图 title('带噪声的频谱') xlabel('Hz'); ylabel('幅值'); elseif K==3 % 构造butterworth滤波器 wp=0.15*pi; ws=0.1*pi; Rp=1; Rs=15; Fs=22050; Ts=1/Fs; wp1=2/Ts*tan(wp/2); %将模拟指标转换成数字指标 ws1=2/Ts*tan(ws/2); [N,Wn]=buttord(wp1,ws1,Rp,Rs,'s'); %选择滤波器的最小阶数 [Z,P,K]=buttap(N); %创建butterworth模拟滤波器 [Bap,Aap]=zp2tf(Z,P,K); [b,a]=lp2lp(Bap,Aap,Wn); [bz,az]=bilinear(b,a,Fs); %用双线性变换法实现模拟滤波器到数字滤波器的转换 [H,W]=freqz(bz,az); %绘制频率响应曲线 figure(3) plot(W*Fs/(2*pi),abs(H)) grid xlabel('频率／Hz') ylabel('频率响应幅度') title('Butterworth') % 开始滤波 f1=filter(bz,az,Y);%滤波 F1=fft(f1,1024); %滤波后fft变换 figure(4) subplot(2,1,1); plot(f1); %画出滤波后的时域图 title('滤波后的时域'); subplot(2,1,2); plot(f,abs(F1(1:512))); %画出滤波后的频谱图 title('滤波后的频谱') xlabel('Hz'); ylabel('幅值'); elseif (K==4) sound(f1,22050); %回放语音信号 elseif (K==5) break; end end % 参考资料 %一、 BUTTORD Butterworth filter order selection. % [N, Wn] = BUTTORD(Wp, Ws, Rp, Rs) returns the order N of the lowest % order digital Butterworth filter that loses no more than Rp dB in % the passband and has at least Rs dB of attenuation in the stopband. % Wp and Ws are the passband and stopband edge frequencies, normalized % from 0 to 1 (where 1 corresponds to pi radians/sample). For example, % Lowpass: Wp = .1, Ws = .2 % Highpass: Wp = .2, Ws = .1 % Bandpass: Wp = [.2 .7], Ws = [.1 .8] % Bandstop: Wp = [.1 .8], Ws = [.2 .7] % BUTTORD also returns Wn, the Butterworth natural frequency (or, % the "3 dB frequency") to use with BUTTER to achieve the specifications. % % [N, Wn] = BUTTORD(Wp, Ws, Rp, Rs, 's') does the computation for an % analog filter, in which case Wp and Ws are in radians/second. % % When Rp is chosen as 3 dB, the Wn in BUTTER is equal to Wp in BUTTORD. % 二、AWGN Add white Gaussian noise to a signal. % Y = AWGN(X,SNR) adds white Gaussian noise to X. The SNR is in dB. % The power of X is assumed to be 0 dBW. If X is complex, then % AWGN adds complex noise. % % Y = AWGN(X,SNR,SIGPOWER) when SIGPOWER is numeric, it represents % the signal power in dBW. When SIGPOWER is 'measured', AWGN measures % the signal power before adding noise. % % Y = AWGN(X,SNR,SIGPOWER,STATE) resets the state of RANDN to STATE. % % Y = AWGN(..., POWERTYPE) specifies the units of SNR and SIGPOWER. % POWERTYPE can be 'db' or 'linear'. If POWERTYPE is 'db', then SNR % is measured in dB and SIGPOWER is measured in dBW. If POWERTYPE is % 'linear', then SNR is measured as a ratio and SIGPOWER is measured % in Watts. % 三、BUTTAP Butterworth analog lowpass filter prototype. % [Z,P,K] = BUTTAP(N) returns the zeros, poles, and gain % for an N-th order normalized prototype Butterworth analog % lowpass filter. The resulting filter has N poles around % the unit circle in the left half plane, and no zeros. % 四、ZP2TF Zero-pole to transfer function conversion. % [NUM,DEN] = ZP2TF(Z,P,K) forms the transfer function: % % NUM(s) % H(s) = -------- % DEN(s) % % given a set of zero locations in vector Z, a set of pole locations % in vector P, and a gain in scalar K. Vectors NUM and DEN are % returned with numerator and denominator coefficients in descending % powers of s. % 五、 LP2LP Lowpass to lowpass analog filter transformation. % [NUMT,DENT] = LP2LP(NUM,DEN,Wo) transforms the lowpass filter % prototype NUM(s)/DEN(s) with unity cutoff frequency of 1 rad/sec % to a lowpass filter with cutoff frequency Wo (rad/sec). % [AT,BT,CT,DT] = LP2LP(A,B,C,D,Wo) does the same when the % filter is described in state-space form. % 六、FFT Discrete Fourier transform. % FFT(X) is the discrete Fourier transform (DFT) of vector X. For % matrices, the FFT operation is applied to each column. For N-D % arrays, the FFT operation operates on the first non-singleton % dimension. % % FFT(X,N) is the N-point FFT, padded with zeros if X has less % than N points and truncated if it has more. % % FFT(X,[],DIM) or FFT(X,N,DIM) applies the FFT operation across the % dimension DIM. % % For length N input vector x, the DFT is a length N vector X, % with elements % N % X(k) = sum x(n)*exp(-j*2*pi*(k-1)*(n-1)/N), 1 <= k <= N. % n=1 % The inverse DFT (computed by IFFT) is given by % N % x(n) = (1/N) sum X(k)*exp( j*2*pi*(k-1)*(n-1)/N), 1 <= n <= N. % k=1