Signal Processing Commons^™

Joint Detection-State Estimation And Secure Signal Processing, Mengqi Ren

Theses and Dissertations

In this dissertation, joint detection-state estimation and secure signal processing are studied. Detection and state estimation are two important research topics in surveillance systems. The detection problems investigated in this dissertation include object detection and fault detection. The goal of object detection is to determine the presence or absence of an object under measurement uncertainty. The aim of fault detection is to determine whether or not the measurements are provided by faulty sensors. State estimation is to estimate the states of moving objects from measurements with random measurement noise or disturbance, which typically consist of their positions and velocities over …

Design, Analysis And Evaluation Of Unmanned Aerial Vehicle Ad Hoc Network For Emergency Response Communications, Robin D. Grodi

College of Graduate Studies: Theses & Dissertations

In any emergency situation, it is paramount that communication be established between those affected by an emergency and the emergency responders. This communication is typically initiated by contacting an emergency service number such as 9-1-1 which will then notify the appropriate responders. The communication link relies heavily on the use of the public telephone network. If an emergency situation causes damage to, or otherwise interrupts, the public telephone network then those affected by the emergency are unable to call for help or warn others. A backup emergency response communication system is required to restore communication in areas where the public …

Design, Analysis, Implementation And Evaluation Of Real-Time Opportunistic Spectrum Access In Cloud-Based Cognitive Radio Networks, Nimish Sharma

College of Graduate Studies: Theses & Dissertations

Opportunistic spectrum access in cognitive radio network is proposed for remediation of spectrum under-utilization caused by exclusive licensing for service providers that are intermittently utilizing spectrum at any given geolocation and time. The unlicensed secondary users (SUs) rely on opportunistic spectrum access to maximize spectrum utilization by sensing/identifying the idle bands without causing harmful interference to licensed primary users (PUs). In this thesis, Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks (ROAR) architecture is presented where cloud computing is used for processing and storage of idle channels. Software-defined radios (SDRs) are used as SUs and PUs that identify, report, …

Performance Analysis Of Secondary Users In Heterogeneous Cognitive Radio Network, Tanjil Amin

College of Graduate Studies: Theses & Dissertations

Continuous increase in wireless subscriptions and static allocation of wireless frequency bands to the primary users (PUs) are fueling the radio frequency (RF) shortage problem. Cognitive radio network (CRN) is regarded as a solution to this problem as it utilizes the scarce RF in an opportunisticmanner to increase the spectrumefficiency. InCRN, secondary users (SUs) are allowed to access idle frequency bands opportunistically without causing harmful interference to the PUs. In CRN, the SUs determine the presence of PUs through spectrum sensing and access idle bands by means of dynamic spectrum access. Spectrum sensing techniques available in the literature do not …

Pattern Recognition In Class Imbalanced Datasets, Nahian A. Siddique

Theses and Dissertations

Class imbalanced datasets constitute a significant portion of the machine learning problems of interest, where recog­nizing the ‘rare class’ is the primary objective for most applications. Traditional linear machine learning algorithms are often not effective in recognizing the rare class. In this research work, a specifically optimized feed-forward artificial neural network (ANN) is proposed and developed to train from moderate to highly imbalanced datasets.

The proposed methodology deals with the difficulty in classification task in multiple stages—by optimizing the training dataset, modifying kernel function to generate the gram matrix and optimizing the NN structure. First, the training dataset is extracted …

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 …

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 …

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 …

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 …

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 …

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 …