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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.
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.
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.
Synthetic Aperture Radar (SAR) is a remote sensing technology that uses radar signals to create
high-resolution images of the Earth's surface. SAR systems are typically mounted on aircraft or
satellites and can operate in all weather conditions, making them ideal for applications such as
environmental monitoring, disaster response, and military reconnaissance.
In this project, we simulate SAR imaging using MATLAB. We generate synthetic radar signals and
process them to create SAR images. The simulation includes the generation of radar pulses,
modeling of the radar system's motion, and the application of signal processing techniques such
as matched filtering and backprojection to reconstruct the SAR image.
The resulting SAR images are analyzed for resolution and quality, and the effects of various
parameters such as pulse bandwidth, platform velocity, and target reflectivity are studied.
A stethoscope is a medical device used by healthcare professionals to listen to internal sounds
of a patient's body, such as heartbeats and lung sounds. In this project, we design and
characterize a multiple input stethoscope apparatus using MATLAB. The apparatus consists of
multiple microphones placed at different locations on the body to capture a comprehensive range
of sounds.
The recorded sounds are processed using MATLAB to enhance signal quality and extract relevant
features. Techniques such as filtering, noise reduction, and spectral analysis are applied to
improve the clarity of the sounds.
The effectiveness of the multiple input stethoscope is evaluated through clinical trials, where
healthcare professionals assess the quality of the recorded sounds and their utility in
diagnosing medical conditions.
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 outputs MIDI data that represents the pitch and timing information contained in the audio signal all in real time.
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.
This project aims to develop a low-cost platform for real-time diagnostic imaging using MATLAB. The system will leverage advanced image processing techniques to enhance the quality of medical images and provide real-time feedback to healthcare professionals. By utilizing MATLAB's powerful image processing toolbox, the project seeks to create an accessible and efficient solution for medical imaging applications.
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.
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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In today\\\'s rapidly advancing era of automation, robotics control systems are evolving to meet the demand for smarter, faster, and more reliable performance. Among the many innovations driving this transformation is the use of MCP (Model-based Control Paradigms)
The financial sector is witnessing a technological revolution with the rise of Large Language Models (LLMs). Traditionally used for text analysis, LLMs are now being integrated with powerful platforms like MATLAB to develop financial forecasting models