Signal Processing Commons^™

Real-Time Digital Effects Processing Using Ios, Jonah W. Clinard

Computer Engineering

In today’s society, we are seeing incredible improvements in terms of creating smaller technological devices that behave more and more like the personal computers of yesterday. Mobile “Smart” devices, in particular, are becoming incredibly powerful not just in terms of processing power, but in the fact that they are able to provide assistance to users in their everyday lives. Application developers are now able utilize the power and size of these devices, to create and realize ideas that would have been previously viewed as impossible. This project applies the fields of digital signal processing, music, and mobile application development, to …

Scaled Synthetic Aperture Radar System Development, Ryan K. Green

Master's Theses

Synthetic Aperture Radar (SAR) systems generate two dimensional images of a target area using RF energy as opposed to light waves used by cameras. When cloud cover or other optical obstructions prevent camera imaging over a target area, SAR can be substituted to generate high resolution images. Linear frequency modulated signals are transmitted and received while a moving imaging platform traverses a target area to develop high resolution images through modern digital signal processing (DSP) techniques. The motivation for this joint thesis project is to design and construct a scaled SAR system to support Cal Poly radar projects. Objectives include …

Hvdc Systems Fault Analysis Using Various Signal Processing Techniques, Benish Paily

Doctoral

The detection and fast clearance of faults are important for the safe and optimal operation of HVDC systems. In HVDC systems, various types of AC faults (rectifier & inverter side) and DC faults can occur. It is therefore necessary to detect the faults and classify them for better protection and diagnostics purposes. Various techniques for fault detection and classification in HVDC systems using signal processing techniques are presented and investigated in this research work. In this research work, it is shown that the wavelet transformation can effectively detect abrupt changes in system signals which are indicative of a fault. This …

Medical Image Registration Using Artificial Neural Network, Hyunjong Choi

Master's Theses

Image registration is the transformation of different sets of images into one coordinate system in order to align and overlay multiple images. Image registration is used in many fields such as medical imaging, remote sensing, and computer vision. It is very important in medical research, where multiple images are acquired from different sensors at various points in time. This allows doctors to monitor the effects of treatments on patients in a certain region of interest over time. In this thesis, artificial neural networks with curvelet keypoints are used to estimate the parameters of registration. Simulations show that the curvelet keypoints …

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Electrical and Computer Engineering Faculty Publications

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly.

Once all data has been trained in …

Filters And Matrix Factorization, Myung-Sin Song, Palle E. T. Jorgensen

SIUE Faculty Research, Scholarship, and Creative Activity

We give a number of explicit matrix-algorithms for analysis/synthesis

in multi-phase filtering; i.e., the operation on discrete-time signals which

allow a separation into frequency-band components, one for each of the

ranges of bands, say N , starting with low-pass, and then corresponding

filtering in the other band-ranges. If there are N bands, the individual

filters will be combined into a single matrix action; so a representation of

the combined operation on all N bands by an N x N matrix, where the

corresponding matrix-entries are periodic functions; or their extensions to

functions of a complex variable. Hence our setting entails …

Protecting Fly-By-Wireless Systems From Remote Attacks, Vahid Heydari

Von Braun Symposium Student Posters

No abstract provided.

Quantification Of Blood Flow Velocity Using Color Sensing, Aditya Deepak Sanghani

Master's Theses

Blood flow velocity is an important parameter that can give information on several pathologies including atherosclerosis, glaucoma, Raynaud’s phenomenon, and ischemic stroke [2,5,6,10]. Present techniques of measuring blood flow velocity involve expensive procedures such as Doppler echocardiography, Doppler ultrasound, and magnetic resonance imaging [11,12]. They cost from $8500-$20000. It is desired to find a low-cost yet equally effective solution for measuring blood flow velocity. This thesis has a goal of creating a proof of concept device for measuring blood flow velocity.

Finger blood flow velocity is investigated in this project. The close proximity to the skin of the finger’s arteries …

Automatic Detection And Denoising Of Signals In Large Geophysical Datasets, Gabriel O. Trisca

Boise State University Theses and Dissertations

To fully understand the complex interactions of various phenomena in the natural world, scientific disciplines such as geology and seismology increasingly rely upon analyzing large amounts of observations. However, data collection is growing at a faster rate than what is currently possible to analyze through traditional approaches. These datasets, supplied by the increasing use of sensors and remote sensing, require specialized computer programs to effectively analyze complex and expansive volumes of data.

Elaborating on existing geophysical data processing approaches for infrasound data collected from an avalanche-prone area, this project proposes new techniques for processing large geophysical datasets. These improved techniques …

A Spline Framework For Optimal Representation Of Semiperiodic Signals, Farzin G. Guilak

Dissertations and Theses

Semiperiodic signals possess an underlying periodicity, but their constituent spectral components include stochastic elements which make it impossible to analytically determine locations of the signal's critical points. Mathematically, a signal's critical points are those at which it is not differentiable or where its derivative is zero. In some domains they represent characteristic points, which are locations indicating important changes in the underlying process reflected by the signal.

For many applications in healthcare, knowledge of precise locations of these points provides key insight for analytic, diagnostic, and therapeutic purposes. For example, given an appropriate signal they might indicate the start or …

Classification Of Digital Communication Signal Modulation Schemes In Multipath Environments Using Higher Order Statistics, Meena Sreekantamurthy

Electrical & Computer Engineering Theses & Dissertations

Automatic identification and classification of modulation schemes in communication signals and decoding of information from the captured signals has assumed great importance recently in the wireless communication industry. Advancements in communications have introduced a large variety of modulation schemes in the transmitted signals; consequently, reliable detection of the modulation scheme in the intercepted signal has become an important issue in communications. It is the aim of this thesis to address this issue of reliable detection. Therefore, this research is focused on modeling and simulation of an automatic modulation classifier and, in particular, on the development of algorithms to use higher …

Ir-Depth Face Detection And Lip Localization Using Kinect V2, Katherine Kayan Fong

Master's Theses

Face recognition and lip localization are two main building blocks in the development of audio visual automatic speech recognition systems (AV-ASR). In many earlier works, face recognition and lip localization were conducted in uniform lighting conditions with simple backgrounds. However, such conditions are seldom the case in real world applications. In this paper, we present an approach to face recognition and lip localization that is invariant to lighting conditions. This is done by employing infrared and depth images captured by the Kinect V2 device. First we present the use of infrared images for face detection. Second, we use the face’s …

Ecg Classification With An Adaptive Neuro-Fuzzy Inference System, Brad Thomas Funsten

Master's Theses

Heart signals allow for a comprehensive analysis of the heart. Electrocardiography (ECG or EKG) uses electrodes to measure the electrical activity of the heart. Extracting ECG signals is a non-invasive process that opens the door to new possibilities for the application of advanced signal processing and data analysis techniques in the diagnosis of heart diseases. With the help of today’s large database of ECG signals, a computationally intelligent system can learn and take the place of a cardiologist. Detection of various abnormalities in the patient’s heart to identify various heart diseases can be made through an Adaptive Neuro-Fuzzy Inference System …

Chipper: Capacitive Bed Occupancy Sensing For An Intelligent Alarm Clock, David Levi

Electrical Engineering

What if your alarm clock knew when you got out—and stayed out—of bed? Current alarm clocks happily let you go back to bed after turning them off. In this project, I build an alarm which only stops ringing when you get out bed, and starts ringing again if you lie back in bed.

This project uses capacitance to detect bed occupancy. A person on or near the bed creates a tiny, picofarads level increase in capacitance, as seen by a sensor placed under the mattress. A microprocessor interprets this signal, and also drives an audio alarm. Shielding of the sensor …

Color Amplification, Jose Carrillo, Cynthia Barajas

Electrical Engineering

The goal of this project is to design and implement a hardware version of MIT’s and Cal Poly’s color amplification system. MIT created a software based system named the “Eulerian Video Magnification” that can reveal small variations that cannot be seen with the naked eye by processing the input sequence of the video. The process consists of using a Gaussian pyramid with a Gaussian kernel in order to do spatial decomposition. This process continues until there is one pixel left which then gets amplified and added back onto each pixel of the original frame for reconstruction. The reconstructed signal can …

Brain Machine Interface Using Emotiv Epoc To Control Robai Cyton Robotic Arm, Daniel P. Prince, Mark J. Edmonds, Andrew J. Sutter, Matthew Thomas Cusumano, Wenjie Lu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

The initial framework for an electroencephalography (EEG) thought recognition software suite is developed, built, and tested. This suite is designed to recognize human thoughts and pair them to actions for controlling a robotic arm.

Raw EEG brain activity data is collected using an Emotiv EPOC headset. The EEG data is processed through linear discriminant analysis (LDA), where an intended action is identified. The EEG classification suite is being developed to increase the number of distinct actions that can be identified compared to the Emotiv recognition software. The EEG classifier was able to correctly distinguish between two separate physical movements.

Future …

Unmanned Aircraft Systems: Air-Ground Channel Characterization For Future Applications, David W. Matolak, Ruoyu Sun

Faculty Publications

Unmanned aircraft systems (UASs) are being used increasingly worldwide. These systems will operate in conditions that differ from conventional piloted aircraft, and this implies that the airground (AG) channel for UASs can differ significantly from the traditional, simple, AG channel models. After providing some background and motivation, we describe the AG channel features and our efforts in measuring and modeling the AG channel. Some example measurement and model results-for the path loss and the Ricean K-factor-are provided to illustrate some of the interesting AG channel characteristics that are still being investigated.

Audio Dsp Amplifier, William Saba, Nicholas Barany

Electrical Engineering

The key concept of this project is to create a microcontroller system that serves as an interface between a DSP board and a total of 4 amplifier channels. The fully integrated system will provide a fully inclusive audio DSP amplifier for use in 2.1 or bi-amplified stereo speaker setups. The project will focus on developing an intuitive interface that is operable from the device or a computer that programs the DSP board for various speaker applications. The finished design will provide a custom computer sound amplifier in one package, eliminating the need for multiple components by interfacing two stereo amplifiers, …

Dual Channel Matrix Switch Audio Receiver, Austin Fox

Electrical Engineering

The Dual Channel Matrix Switch Audio Receiver controls 2 separate audio output channels. Each channel plays any of the system's 3 inputs. This controller enables a user to play two separate audio signals through two separate speaker channels. The system design allows audio input from 2 RCA sources or 1 RCA source and a phono source. The system outputs an audio signal for each output simultaneously at up to 36W on each channel for an 8Ω load. The device allows a user to control the audio input and the volume of each output channel. An Arduino Uno R3 microcontroller interfaced …

Adaptive Motion Pooling And Diffusion For Optical Flow, Naga Venkata Kartheek Medathati, Pierre Kornprobst, Guillaume Masson, Manuela Chessa, Fabio Solari

MODVIS Workshop

We study the impact of local context of an image (contrast and 2D structure) on spatial motion integration by MT neurons. To do so, we revisited the seminal work by Heeger and Simoncelli (HS) [4] using spatio-temporal filters to estimate optical flow from V1-MT feedforward interactions. However, the HS model has difficulties to deal with several problems encountered in real scenes (e.g., blank wall problem and motion discontinuities). Here, we propose to extend the HS model with adaptive processing by focussing on the role of local context indicative of the local velocity estimates reliability. We set a network structure representative …

Global Navigation Satellite System Signal Decomposition And Parameterization Algorithm, Marshall E. Haker, John F. Raquet

AFIT Patents

A method and apparatus is provided for intra-PIT signal decomposition of a signal received with RF front end hardware. The method begins by aligning a signal received by RF front end hardware into integer multiples of a duration of a pseudorandom noise code sequence. A search grid is computed based on an integer multiple of the aligned signal. A plurality of initial ray parameters associated with the computed search grid is coarsely estimated. Using the coarsely estimated plurality of initial ray parameters, a fine estimation of the plurality of initial ray parameters is initiated utilizing stochastic search and optimization techniques. …

Synthetic Aperture Radar: Rapid Detection Of Target Motion In Matlab, Daniel S. Kassen

Master's Theses

Synthetic Aperture Radar (SAR) has come into widespread use in several civilian and military applications. The focus of this paper is the military application of imaging point targets captured by an airborne SAR platform. Using the traditional SAR method of determining target motion by analyzing the difference between subsequent images takes a relatively large amount of processing resources. Using methods in this thesis, target motion can be estimated before even a single image is obtained, reducing the amount of time and power used by a significantly large amount. This thesis builds on work done by Brain Zaharri and David So. …

Assessing Gait And Postural Stability Of Construction Workers Using Wearable Wireless Sensor Networks, Houtan Jebelli

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Falling accidents are a leading cause of fatal and nonfatal injuries in the construction industry. This fact demonstrates the need for a comprehensive fall-risk analysis that incorporates the effects of construction workers’ physiological characteristics. In this context, the objective of the thesis is to investigate and validate the usefulness of the gait- and postural-stability metrics in assessing construction workers’ fall risks. Diverse metrics that assess the capability to keep the body balanced and maintain coordination of body segments during locomotion (gait stability) and stationary postures (postural stability) have been introduced and used in clinical applications. However, their usefulness in the …

Energy Harvesting And Storage: The Catalyst To The Power Constraint For Leveraging Internet Of Things (Iot) On Trains, Kelechi Nwogu

Department of Computer Electronics and Engineering: Dissertations, Theses, and Student Research

The success of Wireless Sensor Networks is heavily constrained by its reliance on storage technology like batteries, which are a finite resource. Whilst the number of transistors in an IC doubles every 18 months, the energy density of batteries is relatively flat during the same time period. This is a key challenge in leveraging the Internet of Things on trains.

The gravity of this problem is increased by an order of magnitude when the network is to be scaled up to hundreds or thousands of nodes. Comprehensive research and development efforts have been devoted to building ultra-low power sensors. These …

Simple Secrecy: Analog Stream Cipher For Secure Voice Communication, John M. Campbell

Senior Honors Theses

Voice signals are inherently analog, and some voice communication systems still utilize analog signals. Existing analog cryptographic methods do not satisfactorily provide cryptosecurity for communication systems due to several limitations. This paper proposes a novel means of provided cryptosecurity for analog signals without digitization; thereby avoiding the latency which results from ADC/DAC conversions. This method utilizes the principles of the digital stream cipher, generating instead a continuous pseudorandom analog key stream signal which is transformed with the original analog signal to create an encrypted ciphertext signal which is statistically independent of the original signal and the key stream signal. The …

A Novel Analysis Of Performance Classification And Workload Prediction Using Electroencephalography (Eeg) Frequency Data, Donovan L. Ricks

Theses and Dissertations

Across the DOD each task an operator is presented with has some level of difficulty associated with it. This level of difficulty over the course of the task is also known as workload, where the operator is faced with varying levels of workload as he or she attempts to complete the task. The focus of the research presented in this thesis is to determine if those changes in workload can be predicted and to determine if individuals can be classified based on performance in order to prevent an increase in workload that would cause a decline in performance in a …

Estimating Single And Multiple Target Locations Using K-Means Clustering With Radio Tomographic Imaging In Wireless Sensor Networks, Jeffrey K. Nishida

Theses and Dissertations

Geolocation involves using data from a sensor network to assess and estimate the location of a moving or stationary target. Received Signal Strength (RSS), Angle of Arrival (AoA), and/or Time Difference of Arrival (TDoA) measurements can be used to estimate target location in sensor networks. Radio Tomographic Imaging (RTI) is an emerging Device-Free Localization (DFL) concept that utilizes the RSS values of a Wireless Sensor Network (WSN) to geolocate stationary or moving target(s). The WSN is set up around the Area of Interest (AoI) and the target of interest, which can be a person or object. The target inside the …

Performance Metrics For Depth-Based Signal Separation Using Deep Vertical Line Arrays, John K. Boyle

Dissertations and Theses

Vertical line arrays (VLAs) deployed below the critical depth in the deep ocean can exploit reliable acoustic path (RAP) propagation, which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, sound from nearby surface interferers also undergoes RAP propagation, and without horizontal aperture, a VLA cannot separate these interferers from submerged targets. A recent publication by McCargar and Zurk (2013) addressed this issue, presenting a transform-based method for passive, depth-based separation of signals received on deep VLAs based on the depth-dependent modulation caused by the interference between the direct and surface-reflected acoustic …

Optimizing Harris Corner Detection On Gpgpus Using Cuda, Justin Loundagin

Master's Theses

ABSTRACT

Optimizing Harris Corner Detection on GPGPUs Using CUDA

The objective of this thesis is to optimize the Harris corner detection algorithm implementation on NVIDIA GPGPUs using the CUDA software platform and measure the performance benefit. The Harris corner detection algorithm—developed by C. Harris and M. Stephens—discovers well defined corner points within an image. The corner detection implementation has been proven to be computationally intensive, thus realtime performance is difficult with a sequential software implementation. This thesis decomposes the Harris corner detection algorithm into a set of parallel stages, each of which are implemented and optimized on the CUDA platform. …

Digital Signal Processing Foundations, David Dorran

Other resources

Signals are all around us and come in a wide variety of shapes and forms. When we speak we create pressure variations in the air which generate audio signals; earthquakes produce large seismic signals; healthcare professionals monitor ECG signals which capture the electrical activity of the heart; radio, internet and telephone signals are being transmitted across the world; the list of signals is endless! (see 2 minute video at pzdsp.com/vid1 for some examples) Digital signal processing (DSP) is primarily about making use of computers to help us analyse and manipulate signals in order to help us with our everyday lives. …