Digital Signal Processing Lab - 2020

This lab has a primary objective of making students understand different filters and filtering techniques in a practical way. This knowledge can be further applied in various practical fields like audio processing or biomedical applications.

First, two experiments were concerned with the Butterworth filter. Impulse Invariant Method and Bilinear Transform were studied and compared. Advantages and disadvantages were studied. Windowing method and FSM method which are used for FIR filter design are studied and compared. Next experiment was concerned with Multirate Signal Processing. This involved designing a series of interpolator and decimeters to obtain the required conversion factor.  Next experiment was adaptive filter design which was concerned with designing an adaptive filter which will adjust to the required conditions. The final experiment was of application of DSP which was concerned with applying the learnt knowledge along with studying paper and patents.

Overall, DSP lab was an enjoyable experience. We were privileged to gain knowledge from  Prof. K.T. V. Talele who himself has an experience of 32 years. It was fun to collaborate with peers and document our observations.

Signal Processing Review

Signal Processing area focuses on issues regarding the efficient processing and transmission of real-time data. Some examples of sources of data include sound, images, and sensor output signals. Signal processing algorithms deal with efficiently transforming the signals resulting from these sources into digital data streams. 
The first thing we learned in this course was a difference between normal microprocessors and DSP processor. We worked on board which had  TMS 320f2833  processor designed by Prof. Y.S. Rao. We used CCS v6 and CCS v8. Lab Sessions included a theory session of 15-20 minutes followed by a practical session. We initially used C codes and then converted them to apply them on board on CCS software. For some programs, we used the actual board and for some we used simulation. Since simulation requires version 6 of software,  (Prof. K.T Talele) sir provided us with is own laptop to work on. We simulated Phase Modulation techniques learned in Digital Communication. We also reviewed a patent in the last experiment to study the practical application of DSP.
The best part of the entire course was an efficient way of setting targets and uploading the experiments well in time. This created a discipline in submission. The targets were challenging and required in-depth knowledge of the subject. Thus, this course was a great learning experience.

LED Binary Counter

There are 4 LEDs on board. Thus, we can make a 16 bit binary counter.  The leftmost LED is MSB and Rightmost is LSB. The programs were implemented on board. The results were observed.

Application of Signal Processing

For the application of Signal Processing, a patent was studied. The Application that we choose was an Equalizer. A graphic audio equalizer alters an audio frequency response in selected frequency bands using a plurality of filters of variable level, fixed frequency band, and fixed center-frequency frequency. A graphic audio equalizer for altering an audio frequency response in selected frequency bands using a plurality of filters of variable level, fixed frequency band, and fixed center frequency.

Sensor Interfacing

Sensors and Sensor Interfacing are an important part of Signal Processing. Microphone, LDR are few sensors on an external board which is connected to our DSP board. These sensors give data which is processed on our board and is then analyzed. This practical was indeed a learning experience.

ADC-DAC

All practical signals are analog in nature. To process them digitally we require ADC and to give them back analog signals we require DAC. This experiment gives a brief overview of the ADC DAC interfacing. The results were observed on an oscilloscope. It was an informative experiment.

Linear Filtering using OAM/OSM

OAM is Overlap Add Method and OSM is Overlap Save Method. Here we added the last two values of the first divided signal and the first two values of the next divided signal. Then we got the output where we added the signals accordingly. Thus we conclude that the input signal represents a near infinite length signal which is broken down into smaller signals for proper calculation. The Board was used and results were observed.