signal-processing

I'm adapting MATLAB code to R and trying to generate a waveform using ARMA formula. Is there a simple R equivalent function for MATLAB's filter to take AR/MA coefficients to build a waveform? npts = 100; a = [1 0.6]; % AR coeffs b = [1 0.25 3]; % MA coeffs e = randn(npts,1); % generate gaussian white noise waveform = filter(b,a,e); % generate waveform Hmm can't you achieve that with filter function in the package signal ? require(signal) a = c(1,0.6) b = c(1,0.25,3) e = rnorm(100) waveform = filter(b,a,e) Yeah, you can do this usring arima.sim , e.g. arima.sim(npts, model=list(ar=a, ma=b),

I need to use Band Pass Filter to filter my real time recording audio. The Range is about 18Khz to 22Khz. I've seen many examples,unfortunatly they are used to detect frequency of audio....Since i'm new to DSP,please ellobrate your answer.... 来源： https://stackoverflow.com/questions/21456630/how-to-use-band-pass-filter18khz-to-22khz-in-android

I have two vectors that represents a function f(x), and another vector f(a x+b) i.e. a scaled and shifted version of f(x). I would like to find the best scale and shift factors. *best - by means of least squares error , maximum likelihood, etc. any ideas? for example: f1 = [0;0.450541598502498;0.0838213779969326;0.228976968716819;0.91333736150167;0.152378018969223;0.825816977489547;0.538342435260057;0.996134716626885;0.0781755287531837;0.442678269775446;0]; f2 = [-0.029171964726699;-0.0278570165494982;0.0331454732535324;0.187656956432487;0.358856370923984;0.449974662483267;0.391341738643094;0

I am using the FFT function in NumPy to do some signal processing. I have array called signal which has one data point for each hour and has a total of 576 data points. I use the following code on signal to look at its fourier transform. t = len(signal) ft = fft(signal,n=t) mgft=abs(ft) plot(mgft[0:t/2+1]) I see two peaks but I am unsure as to what the units of the x axis are i.e., how they map onto hours? Any help would be appreciated. Given sampling rate FSample and transform blocksize N , you can calculate the frequency resolution deltaF , sampling interval deltaT , and total capture time

I'm trying to convert an image into an audio signal in MATLAB by treating it as a spectrogram as in Aphex Twin's song on Windowlicker . Unfortunately, I'm having trouble getting a result. Here it what I have at the moment: function signal = imagetosignal(path, format) % Read in the image and make it symmetric. image = imread(path, format); image = [image; flipud(image)]; [row, column] = size(image); signal = []; % Take the ifft of each column of pixels and piece together the real-valued results. for i = 1 : column spectrogramWindow = image(:, i); R = abs(ifft(spectrogramWindow)); % Take only

I'm looking for a simple C# real-time voice detection library. The input should be an audio stream, and the output should be "human voice" or "not a human voice". I have no knowledge in speech recognition or signal processing, and I'll appreciate any kind of assistance. Kevin Junghans Take a look at the answer for " Detecting audio silence in WAV files using C# ". I am assuming the input is a WAV file. If not please provide the format of the audio stream, or if you are intending on taking input from the microphone directly. If you can measure the amount of silence in an audio stream and you

I want to continuously sample from my PC's audio line in using C# (then process that data). What is the best way to do the sampling? You can do some (basic) audio capture using the open source NAudio .NET Audio Library. Have a look at the NAudioDemo project to see a simple example of recording to a WAV file using the WaveIn functions. NAudio also now includes the ability to capture audio using WASAPI (Windows Vista and above) and ASIO (if your soundcard has an ASIO driver). There is the Alvas Audio library as well, not free, has a nagging screen if you don't pay, but works beautifully. And the