Operation on DSP Processor

Concepts of DSP involve mathematical analysis. Algorithms are already set up for design and analyzing different elements. But its  implementation on chip  ensures output generation on hardware.
So, in this experiment, all the simple operations performed in the previous practicals  were implemented on board. Code Composer Studio software was used. And the hardware used was a custom board of C2000 processor. Embedded C was used with same logic as used earlier in C language in previous experiments.

FIR Filter Design- Frequency Sampling Method

We implemented a second way to design linear phase FIR Filters. Here we first calculate the desired frequency response as done in the windowing method. Then we sample it in the frequency domain and finally take inverse to get the response for the filter.

This experiment was performed using the Scilab. After generating a code involving DFT and IDFT functions it was implemented.Thus, the plot was studied.

FIR Filter Design- Windowing Method

Just like IIR filter we have another digital filter called FIR which is Finite Impulse Response filter. The response to this filter is finite.
This experiment was performed  on Scilab, just like IIR filter design experiment with different formulae for calculation.
When we are designing any filter a specific algorithm is dedicated to it. We followed the algorithm for FIR filter design, generated its code on Scilab and implemented. This method involves obtaining the finite response by using a windowing function. Hanning Window function  was used here.

Patent Review-International Morse Code number generator

Patent Review :

International Morse Code number generator 

Application Number :US 05/517,813

Inventors :     William K. Serp

Publication Date:  29 Sep 1981

Filing Date :   25 Oct 1974

Summary:  This patent generally relates to an automatic International Morse Codegenerator providing a predetermined numerical message, and more particularly relates to such a device which generates a selectively actuable, progressive number.The binary coded decimal of a number is selectively loaded into presettable counters. A switching means sequentially connects each of the binary levels of each of the digits comprising the number to an International Morse Code memory addressing a selected segment thereof. A binary counter sequentially addresses each of the bit locations of the selected memory segment thereby serially generating, in International Morse Code, the digit contained in the addressed memory segment. Upon completion of the code translation of a selected digit of the number, the switching means connects the binary levels of the counter containing the next lesser significant digit to the memory address and the binary counter is recycled. Means are included for selectively deleting the generation of leading zeros of the number and for selectively abbreviating the International Morse Code generation of certain digits comprising the number.

Paper Review-Morse code application for wireless environmental control systems for severely disabled individuals

This was a group experiment for analysis and implementation of morse code generator and its application.It was performed by Saish Desai, Ninad Chitnis, Akash Bangera, Vaibhavi Dichwalkar, Shrinish Donde.



Paper Review-Morse Code Application for Wireless Environmental Control Systems for Severely Disabled Individuals

Publisher-IEEE(Cheng-Hong Yang, Li-Yeh Chuang, Cheng-Huei Yang, and Ching-Hsing Luo)

Published in- IEEE Transactions on Neural Systems and Rehabilitation Engineering ( Volume: 11, Issue: 4, Dec. 2003 )

Summary- Accompanied by the rapid growth of information technology engineering, computers are now used widely in a variety of fields.However, most products are designed for general persons, and are inaccessible to people living with disabilities, unless extra adaptive tools and interfaces were designed for them. Morse code is an adapted access communication tool. So, a  system is designed to enable disabled people  to have an easy access to the  new technology. The proposed system includes four parts: 

1)Input-control module, 

2)Recognition module, 

3)Wireless-control module 

4)Electronic-equipment-control module. 

        Morse code is a simple, fast, and low-cost communication method composed of a series of dots, dashes, and intervals. In this study, they have designed and implemented a human-interface for the environmental control device under a windows environment for handicapped persons whose hand coordination and dexterity are impaired by such ailments as amyotrophic lateral sclerosis, multiple sclerosis, muscular dystrophy etc. This system provides an easy-to-operate environment and allows a handicapped user to access an electronic facility by Morse code. So people with disabilities restricting their body movements with simple actions can control gadgets.

Analog and Digital Chebyshev Filter

This experiment was performed in the similar way as the Chebyshev Filter. These two filters are different in terms of their responses. Chebyshev Filter has ripples. So, here we used the same platform of Scilab and implemented both high pass as well as low pass filters.
Here we gave some parameters as filter inputs and obtained the graph as an output. Thus we could differentiate between different types of IIR filters- Butterwoth and Chebyshev.

Analog and Digital Butterworth Filter

               

       This  practical conducted in order to learn the working of Scilab, which is an open source, cross-platform numerical computational package. The code  for designing digital and analog  filter was written and implemented. We checked the output, which was a graph.

We formed this for high pass and low pass filter. 

       This experiment proved to be very interesting as we learned how tackle new  platforms and how to debug them when we are new to them.

Overlap Add and Overlap Save method

Overlap Add Method(OAM) & Overlap Save Method(OSM)

           When the input sequence is too large, the Convolution of the entire signal at a time is time consuming and tedious. So we break the input sequence.It is an efficient way to evaluate the discrete convolution of a very long signal x [ n ].

           When an input signal x[n] is given to a Digital FIR filter the methods used to get the output sequence are-OAM and OSM.

           The practical implementation of these methods in done in the Lab session. OAM method involves decomposing the input signal and performing linear convolution on each of them individually. The decomposed outputs are then combined together.Similarly OSM method involves decomposing of input.But this method deals with adding some previous values to each decomposed input and then performing circular convolution.

            The decomposed outputs are then combined by removing the first few values from each of them to get the result. This procedure is designed into a code and executed to get the output sequence on the computer when user defined input sequence is typed in Lab session.

Fast Fourier Transform

Fast Fourier Transform(FFT)

         Discrete Fourier Transform is considered as a computationally slow method. So, the best way to reduce addition and multiplication is using Fast Fourier Transform. Speed matters when implementation of this method comes into picture.

         This session involves taking two cases- 4 point input and 8 point input.In both these cases we execute the code for FFT and study its implementation. This execution enable us to prove its computational advantage.

Discrete Fourier Transform

Discrete Fourier Transform(DFT)

        Discrete Fourier Transform is the frequency sampled version of Discrete Time Fourier Transform. Thus, it involves finding the finite set of values .It gives periodic results. This theory is implemented in our practical session.

         Here, we first take a 4 point input x(n) and find its DFT. Finally, we plot its magnitude spectrum by approximation. This process is followed for 8 point sequence- by appending zeros at the end or by placing them at alternate positions in the sequence.This is done by generating a code in C language and displaying the executed result on the Terminal. After execution and value verification of all 3 cases we study the magnitude spectrum pattern. Thus, we infer that as the length of the signal increases the frequency spacing and error decreases.Then we move to the analysis of this method by considering all computations(addition and multiplications) involved and prove that it is slow method.

         

Convolution and Correlation

Convolution and Correlation

          Convolution involves finding relation between input and output of a Linear Time Invariant system.Corrlations provides degree of similarity between  two signals. These operations have to be implemented. This is what we learn in the Digital Signal Processing Practicals.

        Here, the user entered values x(n) are taken as the input along with impulse response h(n). The output we get is y(n) is displayed on the terminal which can be verified. The session involves studying the codes for these operations,compiling and executing them.All types of Convolutions and Correlations are solved using same procedure.

       Thus all the concepts and problems solved manually are verified by the execution. We also thus get a revision of coding involved in problem execution.