signal-processing

I'm an experienced software engineer with some minor college DSP knowledge. I'm working on a smartphone application to process signal data, such as from the microphone (sampled at 44100 Hz) and the accelerometer (sampled at 32-50 Hz). My applications would be, for example, pitch detectors and so forth. I want to implement a low-pass filter (LPF) on the phone to remove aliased frequencies, particularly for the accelerometer, which has a low sampling rate. However, I am finding a contradiction when trying to apply the fast FFT-based convolution method. Any help would be appreciated. Here is my

as the world cup is the main sport event and the Vuvuzelas are the most annoying sound in the world, I had an idea to remove them definitively by reading this new ( http://www.popsci.com/diy/article/2010-06/simple-software-can-filter-out-vuvuzela-whine ) that told us that the sound has some frequencies at 233Hz + 466,932,1864Hz. I have already made a lot of Android application by myself but never touching the signal analysis and filtering part, so here are a few questions, I do not ask for precise answer but maybe links and tutorial to find something to work on. I guess that a new Android

I have a two-column matrix of data obtained from NI-DAQ. The first column is the output data of a motor-generator set (with driver) and the second column is the input data (square wave). I want to find the transfer function using tfest without Simulink. Is it possible? I have System Identification Toolbox . How can I attach a .mat file to this post? My data on gist https://gist.github.com/anonymous/6484844 thewaywewalk You already got the right idea, I don't know where you got stucked. Here is the code which solves your problem, I tested it, its works fine. Be aware that a simpler input

I wanted to use Apache math commons implementation for FFT ( FastFourierTransformer class) to process some dummy data whose 8 data samples are contributing to one complete sinusoidal wave. The maximum being amplitude 230. The code snippet that I tried is below : private double[] transform() { double [] input = new double[8]; input[0] = 0.0; input[1] = 162.6345596729059; input[2] = 230.0; input[3] = 162.63455967290594; input[4] = 2.8166876380389125E-14; input[5] = -162.6345596729059; input[6] = -230.0; input[7] = -162.63455967290597; double[] tempConversion = new double[input.length];

Yamaha InfoSound and ShopKick application use technologies that allow to transfer data using ultrasound . That is playing an inaudible signal (>18kHz) that can be picked up by modern mobile phones (iOS, Android). What is the approach used in such technologies? What kind of modulation they use? I see several problems with this approach. First, 18kHz is not inaudible. Many people cannot hear it, especially as they age, but I know I certainly can (I do regular hearing tests, work-related). Also, most phones have different low-pass filters on their A/D converters , and many devices, especially