Digital Signal Processing MATLAB Projects

Implementation of a Program Address Generator in a DSP Processor

The purpose of this study is to construct a “Program Address Generator”(PAG) to a 24-bit Harvard type, RISC DSP processor using the VHDL language. The PAG is a part of the program control unit, and should consist of the following units:
A system stack for storing jump and loop information. A program counter, a status register, a stack pointer, an operating mode register and two registers called loop address and loop counter register, to support hardware loops.
The PAG handles the fetch stage of the processor pipeline, and should handle instructions such as the jump, subroutine jump, return from subroutine/interrupt and loop instructions, among others.
The PAG was successfully designed, and its function verified through extensive tests, where common combinations of ASM instructions were tested. Files for automated testing was created, to support easy testing if only small changes are applied to the PAG.

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Digital Guitar Effects Unit and Amplifier in MATLAB

This report outlines the design and implementation of a digital guitar effects unit and amplifier. The main portion of this project consisted of the digital equalizer and effects. Several commercial equalizers were researched in order to decide the typical frequency bands and average amount of bands total. Eventually 8 bands were selected. A range of approximately 20Hz-3kHz was chosen based on test data of guitar signals. Popular effects that were incorporated in this project include Distortion, Echo, Reverb, Chorus and Flanger. The digital processor chosen was a Texas Instruments c6713 floating point processor. Designs for the various filters were done in MatLab and implementation on the processor was done through TI’s Code Composer Studio.
Signal processing can be achieved in both the analog and digital domains. The difference between analog and digital is that analog waveforms are continuous in both time and amplitude while digital is discrete in both respects.

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New Approaches to Analyze Sound Barrier Effectiveness

Highway noise can cause annoyance, affect sleep patterns, and reduce the property value for people in the proximity. Current methods for analyzing the effectiveness of sound barriers only take loudness into consideration.
This paper introduces new methods that can be used to analyze the effectiveness of the sound barriers. Our approach uses psychoacoustic measures including sharpness, roughness, fluctuation, strength, and annoyance. Highway noise is non-stationary, therefore each of these metrics are calculated over a short time.
Finally analysis is performed the distribution and change over time. We used nth nearest neighbor algorithm to remove sounds that are not a part of the experiment. In the future, this data can be combined with human surveys to see if the change in sound quality due to the presence of sound barriers has a meaningful impact on people’s lives.

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Synthetic Aperture Radar Imaging Simulated in MATLAB

This thesis further develops a method from ongoing thesis projects with the goal of generating images using synthetic aperture radar (SAR) simulations coded in MATLAB. The project is supervised by Dr. John Saghri and sponsored by Raytheon Space and Airborne Systems. SAR is a type of imaging radar in which the relative movement of the antenna with respect to the target is utilized. Through the simultaneous processing of the radar reflections over the movement of the antenna via the range Doppler algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. The long term goal of this ongoing project is to develop a simulation in which realistic SAR images can be generated and used for SAR Automatic Target Recognition (ATR). Current and past Master’s theses on ATR were restricted to a small data set of Man-portable Surveillance and Target Acquisition Radar (MSTAR) images as most SAR images for military ATR are not released for public use. Also, with an in-house SAR image generation scheme the parameters of noise, target orientation, the elevation angle or look angle to the antenna from the target and other parameters can be directly controlled and modified to best serve ATR purposes or other applications such as three-dimensional SAR holography. At the start of the project in September 2007, the SAR simulation from previous Master’s theses was capable of simulating and imaging point targets in a two dimensional plane with limited mobility. The focus on improvements to this simulation through the course of this project was to improve the SAR simulation for applications to more complex two-dimensional targets and simple three-dimensional targets, such as a cube. The input to the simulation uses a selected two-dimensional, grayscale target image and generates from the input a two-dimensional target profile of reflectivity over the azimuth and range based on the intensity of the pixels in the target image. For three-dimensional simulations, multiple two-dimensional azimuth/range profiles are imported at different altitudes. The output from both the two-dimensional and three-dimensional simulations is the SAR simulated and RDA processed image of the input target profile. Future work on this ongoing project will include an algorithm to calculate line of sight limitations of point targets and processing optimization of the radar information generation implemented in the code so that more complex and realistic targets can be simulated and imaged using SAR for applications in ATR and 3D SAR holography.

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Design, Characterization and Application of a Multiple Input Stethoscope Apparatus Using MATLAB

For this project, the design, implementation, characterization, calibration and possible applications of a multiple transducer stethoscope apparatus were investigated. The multi-transducer sensor array design consists of five standard stethoscope diaphragms mounted to a rigid frame for a-priori knowledge of their relative spatial locations in the x-y plane, with compliant z-direction positioning to ensure good contact and pressure against the subject’s skin for reliable acoustic coupling. When this apparatus is properly placed on the body, it can digitally capture the same important body sounds investigated with standard acoustic stethoscopes; especially heart sounds. Acoustic signal inputs from each diaphragm are converted to electrical signals through microphone pickups installed in the stethoscope connective tubing; and are subsequently sampled and digitized for analysis. With this system, we are able to simultaneously interrogate internal body sounds at a sampling rate of 2 KHz, as most heart sounds of interest occur below 200 Hz. This system was characterized and calibrated by chirp and impulse signal tests. After calibrating the system, a variety of methods for combining the individual sensor channel data to improve the detectability of different signals of interest were explored using variable-delay beam forming. S1 and S2 heart sound recognition with optimized beam forming delays and inter-symbol noise elimination were investigated for improved discernment of the S1 or S2 heart sounds by a user. Also, stereophonic presentation of heart sounds was also produced to allow future investigation of its potential clinical diagnostic efficacy.

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Monophonic Pitch Recognition Using MATLAB

The purpose of this project is to create a system that automatically converts monophonic music into its MIDI equivalent. Automatic pitch recognition allows for numerous commercial applications, including automatic transcription and digital storage of live performances. It is also desirable to be able to take an audio signal as an input and create a MIDI equivalent score because the MIDI information can be used to replace the original audio signal sounds with any sound the user would like. For example, if a piano composition is entered into the system, the resulting MIDI out could be used to trigger guitar samples. The main deliverable for this project is a DSP evaluation board that takes a monophonic analog audio signal (ex. a recorder or someone’s voice creating one pitch at a time), analyzes the signal for its fundamental frequency, and output s MIDI data that represents the pitch and timing information contained in the audio signal all in real time.

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An Overview of Binary Arithmetic Architectures & Their Implementation in DSP Systems using MATLAB

Many branches of the electrical engineering industry involve applications that use digital signal processing. Almost any type of signal that comes in analog form, such as sound, video, and radio or microwaves, must use digital signal processing for implementation in electrical devices. Digital signal processors (DSPs) are devices designed specifically for use in these kinds of applications and provide fast and efficient calculations needed for digital signal processing. DSPs possess many important characteristics that make them ideal for digital signal processing, which involves rapid, repetitive calculations, making speed one of the most essential of these characteristics.

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A Practical Design and Implementation of a Low-Cost Platform for Real-Time Diagnostic Imaging using MATLAB

The emerging need for the current medical devices to achieve immediate visualization and performing diagnostic imaging at real time augurs the demand for high computational power of the associated electronic circuitry. The demand for such a high computational requirement is often met by using software methods to accelerate the computation, which is possible only to a certain extent, impairing the feasibility of real-time imaging and diagnosis. In this paper, a new method of using digital signal processors (DSPs) with a specialized pipelined vision processor (PVP) embedded at the hardware level to accelerate the routinely time-consuming imaging computation is proposed and validated. A lab prototype is built for the feasibility study and clinical validation of the proposed technique. This unique architecture of the PVP in a dual-core DSP offers a high-performance accelerated framework along with its large on-chip memory resources, and reduced bandwidth requirement provides as an ideal architecture for reliable medical computational needs. We have taken two sets sample studies from SPECT for validation-27 cases of thyroid medical history and 20 cases of glomerular filtration rate of kidneys. The results were compared with definitive post-scan SIEMENS image analysis software. From the statistical results, it is clearly shown that this method achieved very superior accuracy and 250% acceleration of computational speed.

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An Overview of Binary Arithmetic Architectures & Their Implementation in DSP Systems Using MATLAB

Many branches of the electrical engineering industry involve applications that use digital signal processing. Almost any type of signal that comes in analog form, such as sound, video, and radio or microwaves, must use digital signal processing for implementation in electrical devices. Digital signal processors (DSPs) are devices designed specifically for use in these kinds of applications and provide fast and efficient calculations needed for digital signal processing. DSPs possess many important characteristics that make them ideal for digital signal processing, which involves rapid, repetitive calculations, making speed one of the most essential of these characteristics. DSPs come in a wide variety of speeds for a multitude of applications. The binary arithmetic architectures DSPs employ to multiply and add during calculations play a large role in determining the speeds at which they operate because faster binary arithmetic calculations leads to faster DSP operation. Like many instances of hardware engineering, balancing arithmetic component speed demands a trade-off between component size and power consumption. Making a multiplier or adder faster requires more hardware, requiring more power and more physical space.

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Swept-Tone Evoked Otoacoustic Emissions: Stimulus Calibration and Equalization Using MATLAB

Otoacoustic Emissions (OAE) are minute acoustic responses originating from the cochlea as a result of an external acoustic stimulus and are recorded using a sensitive microphone placed in the ear canal. OAEs are acquired by synchronous stimulation with an acoustic click or tone burst and recording of the post-stimulus responses. This method of acquiring OAEs is known as transient evoked otoacoustic emissions (TEAOE) and is commonly used in clinics as a screening method for hearing and cochlear functionality in infants. Recently, a novel method of acquiring OAEs utilizing a swept-tone, or chirp, as a stimulus was developed. This method used a deconvolution process to compress the swept tone response into an impulse or click-like response. Because the human ear does not hear all frequencies (pitches) at equal loudness the swept-tone stimulus was equalized in amplitude with respect to frequency. This equalized stimulus will be perceived by the ear as equally loud in all frequencies. In this study a new hearing level equalized stimulus was designed and the OAE responses were analyzed and compared to conventional click evoked OAEs. The equalized swept-tone stimulus evoked greater magnitude OAE responses when compared to the conventional methods. It was also able to evoke responses in subjects that had little TEOAEs which might fail conventional hearing screening.

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