Keywords: Signal processing, signal segmentation, predictive modeling Digital signal processing (DSP) is widely done using languages like MATLAB and C++. R is relatively less known for its support in this domain. However R provides strong support for DSP work. In this talk, we will demonstrate the solution to a standard signal processing and segmentation problem using R. In this problem we will use an input stream of data such as a time series, that will be analysed for power content using short-term Fourier transform methods. The power content in the frequency range of interest, is then smoothed to attenuate short-term variations. This can then be suitably thresholded to find the segment of the signal that corresponds to the region of interest. The implementation will be done purely in R using packages such as, signal, zoo, e1071, etc. Visualisation of the processed data at intermediate stages is also useful and this can be done very efficiently using packages such as ggplot2.
