CONVOLUTION AND CORRELATION

The aim of this experiment was to find Covolution and Correlation of digital signals. We also verified the results using mathematical formulation. In linear convolution causal signal is obtained as the output if both the input signals are causal, circular convolution gives aliased output. Autocorrelation produces an even signal. Autocorrelation of delayed input signals was same as autocorrelation of the original signals. We also did cross correlation of two input signals. Hence, correlation can be used to find the degree of similarity of the signals.

Comments

  1. Unknown25 April 2017 at 22:26

    Well explained.

    ReplyDelete
  2. Unknown28 April 2017 at 09:17

    Radar system and finger print sensor is an application of correlation.

    ReplyDelete
    Replies
    1. Unknown1 May 2017 at 03:17

      Correlation is used wherever we need to find out degree of similarity between signals

      Delete
  3. Parth1 May 2017 at 07:05

    One of the key application of correlation is in radar systems.The transmitted signal is correlated with the echo signal to locate the position of the target.Convolution gives the relation between the input signal, output signal and the response of the signal.

    ReplyDelete

Post a Comment

Popular posts from this blog

FIR Filter Design using FSM

A filter is essentially a system or a network that selectively changes the wave shape, amplitude–frequency and/or phase-frequency characteristics of a signal in desired manner. Common filtering objectives are to improve the quality of a signal, to extract information from signal or to separate two or more signals previously combined.  FSM for FIR filter  design is perhaps the simplest and most direct technique when a desired frequency response  has been specified. T he given frequency response is sampled at a set of equally spaced frequencies to obtain N samples. Thus , sampling the continuous frequency response Hd(w) at N points essentially gives us the N-point DFT of Hd(2pnk/N). Thus by using the IDFT formula, the filter co-efficients can be calculated. One way to reduce the error is to increase the number of frequency samples. Thus we FIR filter design using Frequency Sampling Method and noted the output.
Read more

Review on Patent

Signal processing system and method for enhanced cascaded integrator-comb interpolation filter stabilization   Patent No.  US 5880973 A A signal processing system and method for stabilizing cascaded integrator-comb (CIC) interpolation filters. The signal processing system includes an overflow detection circuit and reset circuitry. The overflow detection circuit monitors the output of the CIC interpolation filter for an overflow condition which is indicative of filter instability. When an overflow condition is detected, the reset circuitry automatically resets the filter, thereby eliminating the instability.  ransmission filter 102 first interpolates the input samples (31.5 MHz samples on bus 112) by a factor of 4, as well as shapes the spectral response. In general, implementation of transmission filter 102 is well known in the art. For example, a conventional finite impulse response (FIR) filter, with one or two stages, can be used. With respect to a QPSK-based cellu...
Read more

Linear phase FIR filter design using windowing method

In this experiment we designed Linear phase FIR filter using Scilab. These are filters that have a Finite Impulse Response. Broadly, the method for designing the filter is the same as IIR filters. Filter parameters like Attenuation in Stop band (As) and Pass band (Ap) as well as Pass band frequency, Stop band frequency and sampling frequency were given as input. You input the formulae in a Scilab code and run the program. Window function include Hamming window, Bartlet Window, Hanning window, Blackman window etc. We used a Hanning Window as the window function and wrote the code accordingly. The difference between IIR and FIR designing is that much of the calculation is done in time domain rather than the transform domain..
Read more