Signal Processing Commons^™

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.

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. …

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 …

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 …

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 …

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 …

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 …

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. …

2015 Acuta/Nacubo/Acuho-1 Report

ACUTA: Other Publications

In This Issue

Introduction

Methodology

Executive Summary

Findings

Bandwidth Management

Wireless Coverage and Capacity

ResNet Service and Support

Planning and Measurement

Funding and Technology Costs

Outsourcing

A Collaborative Adaptive Wiener Filter For Image Restoration Using A Spatial-Domain Multi-Patch Correlation Model, Khaled M. Mohamed, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

We present a new patch-based image restoration algorithm using an adaptive Wiener filter (AWF) with a novel spatial-domain multi-patch correlation model. The new filter structure is referred to as a collaborative adaptive Wiener filter (CAWF). The CAWF employs a finite size moving window. At each position, the current observation window represents the reference patch. We identify the most similar patches in the image within a given search window about the reference patch. A single-stage weighted sum of all of the pixels in the similar patches is used to estimate the center pixel in the reference patch. The weights are based …

Experimental-Computational Analysis Of Vigilance Dynamics For Applications In Sleep And Epilepsy, Farid Yaghouby

Theses and Dissertations--Biomedical Engineering

Epilepsy is a neurological disorder characterized by recurrent seizures. Sleep problems can cooccur with epilepsy, and adversely affect seizure diagnosis and treatment. In fact, the relationship between sleep and seizures in individuals with epilepsy is a complex one. Seizures disturb sleep and sleep deprivation aggravates seizures. Antiepileptic drugs may also impair sleep quality at the cost of controlling seizures. In general, particular vigilance states may inhibit or facilitate seizure generation, and changes in vigilance state can affect the predictability of seizures. A clear understanding of sleep-seizure interactions will therefore benefit epilepsy care providers and improve quality of life in patients. …

One-Bit Compressive Sensing With Partial Support Information, Phillip North

CMC Senior Theses

This work develops novel algorithms for incorporating prior-support information into the field of One-Bit Compressed Sensing. Traditionally, Compressed Sensing is used for acquiring high-dimensional signals from few linear measurements. In applications, it is often the case that we have some knowledge of the structure of our signal(s) beforehand, and thus we would like to leverage it to attain more accurate and efficient recovery. Additionally, the Compressive Sensing framework maintains relevance even when the available measurements are subject to extreme quantization. Indeed, the field of One-Bit Compressive Sensing aims to recover a signal from measurements reduced to only their sign-bit. This …

Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang

Theses and Dissertations--Electrical and Computer Engineering

Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high …