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- All Subjects: Signal Processing
Description
This creative project thesis involves electronic music composition and production, and it uses some elements of algorithmic music composition (through recurrent neural networks). Algorithmic composition techniques are used here as a tool in composing the pieces, but are not the main focus. Thematically, this project explores the analogy between artificial neural networks and neural activity in the brain. This project consists of three short pieces, each exploring these concept in different ways.
ContributorsKarpur, Ajay (Author) / Suzuki, Kotoka (Thesis director) / Ingalls, Todd (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The world of a hearing impaired person is much different than that of somebody capable of discerning different frequencies and magnitudes of sound waves via their ears. This is especially true when hearing impaired people play video games. In most video games, surround sound is fed through some sort of digital output to headphones or speakers. Based on this information, the gamer can discern where a particular stimulus is coming from and whether or not that is a threat to their wellbeing within the virtual world. People with reliable hearing have a distinct advantage over hearing impaired people in the fact that they can gather information not just from what is in front of them, but from every angle relative to the way they're facing. The purpose of this project was to find a way to even the playing field, so that a person hard of hearing could also receive the sensory feedback that any other person would get while playing video games To do this, visual surround sound was created. This is a system that takes a surround sound input, and illuminates LEDs around the periphery of glasses based on the direction, frequency and amplitude of the audio wave. This provides the user with crucial information on the whereabouts of different elements within the game. In this paper, the research and development of Visual Surround Sound is discussed along with its viability in regards to a deaf person's ability to learn the technology, and decipher the visual cues.
ContributorsKadi, Danyal (Co-author) / Burrell, Nathaneal (Co-author) / Butler, Kristi (Co-author) / Wright, Gavin (Co-author) / Kosut, Oliver (Thesis director) / Bliss, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2015-05
Description
Detecting early signs of neurodegeneration is vital for measuring the efficacy of pharmaceuticals and planning treatments for neurological diseases. This is especially true for Amyotrophic Lateral Sclerosis (ALS) where differences in symptom onset can be indicative of the prognosis. Because it can be measured noninvasively, changes in speech production have been proposed as a promising indicator of neurological decline. However, speech changes are typically measured subjectively by a clinician. These perceptual ratings can vary widely between clinicians and within the same clinician on different patient visits, making clinical ratings less sensitive to subtle early indicators. In this paper, we propose an algorithm for the objective measurement of flutter, a quasi-sinusoidal modulation of fundamental frequency that manifests in the speech of some ALS patients. The algorithm detailed in this paper employs long-term average spectral analysis on the residual F0 track of a sustained phonation to detect the presence of flutter and is robust to longitudinal drifts in F0. The algorithm is evaluated on a longitudinal speech dataset of ALS patients at varying stages in their prognosis. Benchmarking with two stages of perceptual ratings provided by an expert speech pathologist indicate that the algorithm follows perceptual ratings with moderate accuracy and can objectively detect flutter in instances where the variability of the perceptual rating causes uncertainty.
ContributorsPeplinski, Jacob Scott (Author) / Berisha, Visar (Thesis director) / Liss, Julie (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The increasing presence and affordability of sensors provides the opportunity to make novel and creative designs for underserved markets like the legally blind. Here we explore how mathematical methods and device coordination can be utilized to improve the functionality of inexpensive proximity sensing electronics in order to create designs that are versatile, durable, low cost, and simple. Devices utilizing various acoustic and electromagnetic wave frequencies like ultrasonic rangefinders, radars, Lidar rangefinders, webcams, and infrared rangefinders and the concepts of Sensor Fusion, Frequency Modulated Continuous Wave radar, and Phased Arrays were explored. The effects of various factors on the propagation of different wave signals was also investigated. The devices selected to be incorporated into designs were the HB100 DRO Radar Doppler Sensor (as an FMCW radar), HC-SR04 Ultrasonic Sensor, and Maxbotix Ultrasonic Rangefinder \u2014 EZ3. Three designs were ultimately developed and dubbed the "Rad-Son Fusion", the "Tri-Beam Scanner", and the "Dual-Receiver Ranger". The "Rad-Son Fusion" employs the Sensor Fusion of an FMCW radar and Ultrasonic sensor through a weighted average of the distance reading from the two sensors. The "Tri-Beam Scanner" utilizes a beam-forming Digital Phased Array of ultrasonic sensors to scan its surroundings. The "Dual-Receiver Ranger" uses the convolved result from to two modified HC-SR04 sensors to determine the time of flight and ultimately an object's distance. After conducting hardware experiments to determine the feasibility of each design, the "Dual-Receiver Ranger" was prototyped and tested to demonstrate the potential of the concept. The designs were later compared based on proposed requirements and possible improvements and challenges associated with the designs are discussed.
ContributorsFeinglass, Joshua Forster (Author) / Goryll, Michael (Thesis director) / Reisslein, Martin (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The purpose of this project is to create a useful tool for musicians that utilizes the harmonic content of their playing to recommend new, relevant chords to play. This is done by training various Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) on the lead sheets of 100 different jazz standards. A total of 200 unique datasets were produced and tested, resulting in the prediction of nearly 51 million chords. A note-prediction accuracy of 82.1% and a chord-prediction accuracy of 34.5% were achieved across all datasets. Methods of data representation that were rooted in valid music theory frameworks were found to increase the efficacy of harmonic prediction by up to 6%. Optimal LSTM input sizes were also determined for each method of data representation.
ContributorsRangaswami, Sriram Madhav (Author) / Lalitha, Sankar (Thesis director) / Jayasuriya, Suren (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.
ContributorsHirte, Amanda (Author) / Kosut, Oliver (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Power spectral analysis is a fundamental aspect of signal processing used in the detection and \\estimation of various signal features. Signals spaced closely in frequency are problematic and lead analysts to miss crucial details surrounding the data. The Capon and Bartlett methods are non-parametric filterbank approaches to power spectrum estimation. The Capon algorithm is known as the "adaptive" approach to power spectrum estimation because its filter impulse responses are adapted to fit the characteristics of the data. The Bartlett method is known as the "conventional" approach to power spectrum estimation (PSE) and has a fixed deterministic filter. Both techniques rely on the Sample Covariance Matrix (SCM). The first objective of this project is to analyze the origins and characteristics of the Capon and Bartlett methods to understand their abilities to resolve signals closely spaced in frequency. Taking into consideration the Capon and Bartlett's reliance on the SCM, there is a novelty in combining these two algorithms using their cross-coherence. The second objective of this project is to analyze the performance of the Capon-Bartlett Cross Spectra. This study will involve Matlab simulations of known test cases and comparisons with approximate theoretical predictions.
ContributorsYoshiyama, Cassidy (Author) / Richmond, Christ (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In the field of electronic music, haptic feedback is a crucial feature of digital musical instruments (DMIs) because it gives the musician a more immersive experience. This feedback might come in the form of a wearable haptic device that vibrates in response to music. Such advancements in the electronic music field are applicable to the field of speech and hearing. More specifically, wearable haptic feedback devices can enhance the musical listening experience for people who use cochlear implant (CI) devices.
This Honors Thesis is a continuation of Prof. Lauren Hayes’s and Dr. Xin Luo’s research initiative, Haptic Electronic Audio Research into Musical Experience (HEAR-ME), which investigates how to enhance the musical listening experience for CI users using a wearable haptic system. The goals of this Honors Thesis are to adapt Prof. Hayes’s system code from the Max visual programming language into the C++ object-oriented programming language and to study the results of the developed C++ codes. This adaptation allows the system to operate in real-time and independently of a computer.
Towards these goals, two signal processing algorithms were developed and programmed in C++. The first algorithm is a thresholding method, which outputs a pulse of a predefined width when the input signal falls below some threshold in amplitude. The second algorithm is a root-mean-square (RMS) method, which outputs a pulse-width modulation signal with a fixed period and with a duty cycle dependent on the RMS of the input signal. The thresholding method was found to work best with speech, and the RMS method was found to work best with music. Future work entails the design of adaptive signal processing algorithms to allow the system to work more effectively on speech in a noisy environment and to emphasize a variety of elements in music.
This Honors Thesis is a continuation of Prof. Lauren Hayes’s and Dr. Xin Luo’s research initiative, Haptic Electronic Audio Research into Musical Experience (HEAR-ME), which investigates how to enhance the musical listening experience for CI users using a wearable haptic system. The goals of this Honors Thesis are to adapt Prof. Hayes’s system code from the Max visual programming language into the C++ object-oriented programming language and to study the results of the developed C++ codes. This adaptation allows the system to operate in real-time and independently of a computer.
Towards these goals, two signal processing algorithms were developed and programmed in C++. The first algorithm is a thresholding method, which outputs a pulse of a predefined width when the input signal falls below some threshold in amplitude. The second algorithm is a root-mean-square (RMS) method, which outputs a pulse-width modulation signal with a fixed period and with a duty cycle dependent on the RMS of the input signal. The thresholding method was found to work best with speech, and the RMS method was found to work best with music. Future work entails the design of adaptive signal processing algorithms to allow the system to work more effectively on speech in a noisy environment and to emphasize a variety of elements in music.
ContributorsBonelli, Dominic Berlage (Author) / Papandreou-Suppappola, Antonia (Thesis director) / Hayes, Lauren (Thesis director, Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
The use of conventional weather radar in vulcanology leads to two problems: the radars often use wavelengths which are too long to detect the fine ash particles, and they cannot be field–adjusted to fit the wide variety of eruptions. Thus, to better study these geologic processes, a new radar must be developed that is easily reconfigurable to allow for flexibility and can operate at sufficiently short wavelengths.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
ContributorsLee, Byeong Mok (Co-author) / Xi, Andrew Jinchi (Co-author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Baumann, Alicia (Committee member) / Cochran, Douglas (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The use of conventional weather radar in vulcanology leads to two problems: the radars often use wavelengths which are too long to detect the fine ash particles, and they cannot be field–adjusted to fit the wide variety of eruptions. Thus, to better study these geologic processes, a new radar must be developed that is easily reconfigurable to allow for flexibility and can operate at sufficiently short wavelengths.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
This thesis investigates how to design a radar using a field–programmable gate array board to generate the radar signal, and process the returned signal to determine the distance and concentration of objects (in this case, ash). The purpose of using such a board lies in its reconfigurability—a design can (relatively easily) be adjusted, recompiled, and reuploaded to the hardware with none of the cost or time overhead required of a standard weather radar.
The design operates on the principle of frequency–modulated continuous–waves, in which the output signal frequency changes as a function of time. The difference in transmit and echo frequencies determines the distance of an object, while the magnitude of a particular difference frequency corresponds to concentration. Thus, by viewing a spectrum of frequency differences, one is able to see both the concentration and distances of ash from the radar.
The transmit signal data was created in MATLAB®, while the radar was designed with MATLAB® Simulink® using hardware IP blocks and implemented on the ROACH2 signal processing hardware, which utilizes a Xilinx® Virtex®–6 chip. The output is read from a computer linked to the hardware through Ethernet, using a Python™ script. Testing revealed minor flaws due to the usage of lower–grade components in the prototype. However, the functionality of the proposed radar design was proven, making this approach to radar a promising path for modern vulcanology.
ContributorsXi, Andrew Jinchi (Co-author) / Lee, Matthew Byeongmok (Co-author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Cochran, Douglas (Committee member) / Baumann, Alicia (Committee member) / Electrical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05