DSPP EXPERIMENTS

An analysis of a type of comb filter Several basic arrangements of delay unit, combining unit and feedback unit are shown to have amplitude/frequency response characteristics of the type which has given rise to the name comb filter. Such filters are useful for the selection or rejection of a train of uniformly spaced regular pulses. The response of the most suitable configurations to such a train of pulses and to a Gaussian noise input is investigated with particular reference to the improvement in signal/noise ratio possible with this type of filter. The practical realization of such filters is discussed and the most suitable forms of practical comb filter are indicated, together with a brief discussion of their incorporation into a radar system.

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...

We have seen the mathematical analysis and various digital systems with digital signals. However, they are of no use if they can't be used in the real world.  We need to have some physical hardware that will implement these operations. This is where the DSP processor comes in.  We used a custom board of the popular C2000 processor. The coding platform used was Code Composer Studio. Using the implementations of DSP algorithms in C language developed previously, the code was tweaked to work on-chip in embedded C. Using this processor we can carry out  simple mathematical operations such as addition, subtraction, bit manipulation,etc.

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.

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..