DSP Projects

Digital signal processing (DSP) has developed to be important, both technologically and theoretically. The major reason for its success in industry is its growth and low-cost for software and hardware. hardware algorithms are used in new technologies and applications in many fields.DSP Projects are used in various applications like Image enhancement, Image Recognition, Speech Recognition, Speech Recognition, Noise Reduction and Audio enhancement. Due to the above reason the electrical and computer engineer’s with DSP background demand is raised. Hence it is important to make DSP Projects plays as an integral part of any electrical engineering field. Digital Signal processing application area have developed instantly now a day’s parallel to the development of powerful and low-cost processing circuits and low price of computer memory. This leads to number of new applications which includes handheld communication devices and multimedia delivery along with the convergence of telecommunication technologies and computer.

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2015 IEEE DSP PROJECTS

• FDR 2.0: A Low-Power Dynamically Reconfigurable Architecture and Its FinFET Implementation.
• FPGA-based design and implementation of direct torque control for induction machines.
• Adaptive Control of Grid-Connected Inverters Based on Online Grid Impedance Measurements.
• Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications.
• Accurate and Efficient Three Level Design Space Exploration Based on Constraints Satisfaction Optimization Problem Solver.
• Fuzzy-Logic-Controller-Based SEPIC Converter for Maximum Power Point Tracking.
• Network-on-Chip Design for Heterogeneous Multiprocessor System-on-Chip.
• High-level design for image processing on FPGA using Xilinx AccelDSP.
• Digital transceiver module for on-board communication system.
• RF filter characterization using a chirp.

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Applications of DSP Projects

• Image Enhancement.
• Image Recognition.
• Speech Recognition.
• Digital music.
• Audio Enchancement and noise Reduction.

Image enhancement:

In this technique the quality of the digital image is suffering degradation aver time on older recording media or degradation by noise on a communication channel.

Image recognition:

In this technique the images are recognized like recognizing patterns in images, recognizing faces for security systems, character recognition in scanned text and handwriting recognition.

Speech recognition:

It gives natural interface to information retrieval system and computer systems. Entertainment industry which uses enhancement and special effects .Digital music applications uses MATLAB function to recognize the signal mathematically.

Audio enhancement and noise reduction:

In this the important use is to improve the audio quality, specifically in acoustically tough environments like vehicles. In cars and planes, for example it is expected goal is to develop the passenger comfort and to enhance safety. Projects are guided for all B.E students and the paper title is updated regularly from Springer journal. The sampling of images with three dimensional views is allowed in image aliasing explorer. The explanation gives a fast feedback about the relationship among spatial frequencies and pixels. The image is displayed on the right after it is loaded from the file menu.

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