Signal Processing Commons^™

Networks - I: An Instantiation Of Way Point Routing For Mobile Ad Hoc Networks, Waseem M. Arain, Sayeed Ghani

International Conference on Information and Communication Technologies

Mobile ad hoc networks are increasingly finding their existence in the marketplace heading to a new paradigm of pervasive computing. However there are many areas open to research in the field. Due to node mobility resulting in an ever-changing network topology, conventional routing methods cannot be applied in MANETS. Therefore, this is one of the core areas of research. Researchers are challenged to design protocols that can potentially scale to anything from thousand to tens of thousands of nodes and to reduce the route discovery latency. In this paper a different instantiation of way point routing (WPR) model is proposed, …

Scene-Based Nonuniformity Correction With Reduced Ghosting Using A Gated Lms Algorithm, Russell C. Hardie, Frank Orion Baxley, Brandon J. Brys, Patrick C. Hytla

Electrical and Computer Engineering Faculty Publications

In this paper, we present a scene-based nouniformity correction (NUC) method using a modified adaptive least mean square (LMS) algorithm with a novel gating operation on the updates. The gating is designed to significantly reduce ghosting artifacts produced by many scene-based NUC algorithms by halting updates when temporal variation is lacking. We define the algorithm and present a number of experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published methods including other LMS and constant statistics based methods. The experimental results include simulated imagery and a real infrared image sequence. We show that …

A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj

Electrical & Computer Engineering Faculty Research

This paper discusses the symbolic functional decomposition method for implementing finite state machines in field-programmable gate array devices. This method is a viable alternative to the presently widespread two-step approaches to the problem, which consist of separate encoding and mapping stages; the proposed method does not have a separate decomposition step instead, the state's final encoding is introduced gradually on every decomposition iteration. Along with general description of the functional symbolic decomposition method's steps, the paper discusses various algorithms implementing the method and presents an example realisation of the most interesting algorithm. In the end, the paper compares the results …

Human Identification Using Pyroelectric Infrared Sensors, Aron E. Suppes

UNLV Theses, Dissertations, Professional Papers, and Capstones

The objective of this thesis is to discuss the viability of using pyroelectric infrared (PIR) sensors as a biometric system for human identification.

The human body emits infrared radiation, the distribution of which varies throughout the body, and depends upon the shape and composition of the particular body part. A PIR sensor utilizing a Fresnel lens will respond to this infrared radiation. When a human walks, the motion of the body's individual components form a characteristic gait that is likely to affect a PIR sensor field in a unique way.

A statistical model, such as a Hidden Markov Model, could …

Subjective Audio Quality Over A Secure Ieee 802.11n Draft 2.0 Wireless Local Area Network, Benjamin W. Ramsey

Theses and Dissertations

This thesis investigates the quality of audio generated by a G.711 codec and transmission over an IEEE 802.11n draft 2.0 wireless local area network (WLAN). Decline in audio quality due to additional calls or by securing the WLAN with transport mode Internet Protocol Security (IPsec) is quantified. Audio quality over an IEEE 802.11n draft 2.0 WLAN is also compared to that of IEEE 802.11b and IEEE 802.11g WLANs under the same conditions. Audio quality is evaluated by following International Telecommunication Union Telecommunication Standardization Sector (ITU-T) Recommendation P.800, where human subjects rate audio clips recorded during various WLAN configurations. The Mean …

A Mobile Ecg Monitoring System With Context Collection, Jin Peng Li, Damon Berry, Richard Hayes

Conference Papers

Preventative health management represents a shift from the traditional approach of reactive treatment-based healthcare towards a proactive wellness-management approach where patients are encouraged to stay healthy with expert support when they need it, at any location and any time. This work represents a step along the road towards proactive, preventative healthcare for cardiac patients. It seeks to develop a smart mobile ECG monitoring system that requests and records context information about what is happening around the subject when an arrhythmia event occurs. Context information about the subject’s activities of daily living will, it is hoped, provide an enriched data set …

Free Regions Of Sensor Nodes, Laxmi P. Gewali, Navin Rongatana, Henry Selvaraj, Jan B. Pedersen

Electrical & Computer Engineering Faculty Research

We introduce the notion of free region of a node in a sensor network. Intuitively, a free region of a node is the connected set of points R in its neighborhood such that the connectivity of the network remains the same when the node is moved to any point in R. We characterize several properties of free regions and develop an efficient algorithm for computing them. We capture free region in terms of related notions called in-free region and out-free region. We present an O(n2) algorithm for constructing the free region of a node, where n is the number of …

Significance Of Logic Synthesis In Fpga-Based Design Of Image And Signal Processing Systems, Mariusz Rawski, Henry Selvaraj, Bogdan J. Falkowski, Tadeusz Luba

Electrical & Computer Engineering Faculty Research

This chapter, taking FIR filters as an example, presents the discussion on efficiency of different implementation methodologies of DSP algorithms targeting modern FPGA architectures. Nowadays, programmable technology provides the possibility to implement digital systems with the use of specialized embedded DSP blocks. However, this technology gives the designer the possibility to increase efficiency of designed systems by exploitation of parallelisms of implemented algorithms. Moreover, it is possible to apply special techniques, such as distributed arithmetic (DA). Since in this approach, general-purpose multipliers are replaced by combinational LUT blocks, it is possible to construct digital filters of very high performance. Additionally, …

Antennas For Portable Communications In The Uwb And Gps Spectra., Giuseppe Ruvio

Doctoral

The thesis describes a study of antennas for solutions in emerging systems. An account of the fundamental principles of these antennas is given together with an outline of the basic electromagnetic theory on which the designs are based. While the main focus is on antennas for Ultra Wideband (UWB) systems, some additional work was carried out on enhancing performance of circularly polarised antennas for satellite navigation systems. The study focussed on the design of highly efficient broadband antennas with particular requirements for size compactness, gain stability, phase-linearity, and the use of low-cost materials. These requirements are particularly important for UWB …

A Map Estimator For Simultaneous Superresolution And Detector Nonunifomity Correct, Russell C. Hardie, Douglas R. Droege

Electrical and Computer Engineering Faculty Publications

During digital video acquisition, imagery may be degraded by a number of phenomena including undersampling, blur, and noise. Many systems, particularly those containing infrared focal plane array (FPA) sensors, are also subject to detector nonuniformity. Nonuniformity, or fixed pattern noise, results from nonuniform responsivity of the photodetectors that make up the FPA. Here we propose a maximuma posteriori (MAP) estimation framework for simultaneously addressing undersampling, linear blur, additive noise, and bias nonuniformity. In particular, we jointly estimate a superresolution (SR) image and detector bias nonuniformity parameters from a sequence of observed frames. This algorithm can be applied to video in …

Gaussian Mixture Models And Neural Networks For Automatic Speaker Identification, Usha Gayatri Chalkapally

Electrical & Computer Engineering Theses & Dissertations

Automatic Speaker Recognition is the process of automatically recognizing who is speaking on the basis of individual information contained in speech signals. This technique of Automatic Speaker Recognition makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers.

In this thesis, the techniques of Gaussian Mixture Models and Neural Networks for Automatic Speaker Identification are presented. Algorithms for Speaker Identification using Gaussian Mixture Models were developed, …

Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj

Electrical & Computer Engineering Faculty Research

The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …

Supplementing An Ad-Hoc Wireless Network Routing Protocol With Radio Frequency Identification (Rfid) Tags, Leroy S. Willemsen

Theses and Dissertations

Wireless sensor networks (WSNs) have a broad and varied range of applications, yet all of these are limited by the resources available to the sensor nodes that make up the WSN. The most significant resource is energy. A WSN may be deployed to an inhospitable or unreachable area, leaving it with a non-replenishable power source. This research examines a way of reducing energy consumption by augmenting the nodes with radio frequency identification (RFID) tags that contain routing information. It was expected that RFID tags would reduce the network throughput, the ad hoc on-demand distance vector (AODV) routing traffic sent, and …

Characterization And Design Of High-Level Vhdl I/Q Frequency Downconverter Via Special Sampling Scheme, Jesse P. Somann

Theses and Dissertations

This study explores the characterization and implementation of a Special Sampling Scheme (SSS) for In-Phase and Quad-Phase (I/Q) down conversion utilizing top-level, portable design strategies. The SSS is an under-developed signal sampling methodology that can be used with military and industry receiver systems, specifically, United States Air Force (USAF) video receiver systems. The SSS processes a digital input signal-stream sampled at a specified sampling frequency, and down converts it into In-Phase (I) and Quad-Phase (Q) output signal-streams. Using the theory and application of the SSS, there are three main objectives that will be accomplished: characterization of the effects of input, …

Partition-Based Interpolation For Color Filter Array Demosaicking And Super-Resolution Reconstruction, Min Shao, Kenneth E. Barner, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

A class of partition-based interpolators that addresses a variety of image interpolation applications are proposed. The proposed interpolators first partition an image into a finite set of partitions that capture local image structures. Missing high resolution pixels are then obtained through linear operations on neighboring pixels that exploit the captured image structure. By exploiting the local image structure, the proposed algorithm produces excellent performance on both edge and uniform regions. The presented results demonstrate that partition-based interpolation yields results superior to traditional and advanced algorithms in the applications of color filter array (CFA) demosaicking and super-resolution reconstruction.

Electromagnetic Propagation Prediction Inside Aircraft Cabins, Genevieve Hankins

Electrical & Computer Engineering Theses & Dissertations

Electromagnetic propagation models for signal strength prediction within aircraft cabins are essential for evaluating and designing a wireless communication system to be implemented onboard aircraft. There are many commercially available software packages for predicting wireless system performance in conventional indoor environments. It is of interest to examine the available software to determine if the aircraft's electromagnetic environment (EME) can be modeled successfully without developing an aircraft specific prediction tool. EnterprisePlanner®, a registered product of Wireless Valley Communications, Incorporated, was selected for the present effort. The performance of the prediction model was evaluated through a comparison with field measurements taken on …

Electromagnetic Wave Propagation Prediction For Wireless Networks Inside Boeing Fuselages, Mennatoallah Youssef

Electrical & Computer Engineering Theses & Dissertations

Commercial grade software is intended for electromagnetic predictions within office buildings; it was used to develop models to analyze propagation inside airplane fuselages. This study shows that Wireless XGTD and Insite software can accurately predict power propagation within airplane fuselages. Current work uses fuselage models, which contain additional internal components. A comparison was made between empty and full fuselage to examine the effects of internal components. Two propagation model types [Fast 3D and Full 3D] were also compared for accuracy to experimental study. It was concluded that completed fuselages are suggested for further simulation study as well as that the …

A Fast And Simple Algorithm For Computing M-Shortest Paths In State Graph, M. Sherwood, Laxmi P. Gewali, Henry Selvaraj, Venkatesan Muthukumar

Electrical & Computer Engineering Faculty Research

We consider the problem of computing m shortest paths between a source node s and a target node t in a stage graph. Polynomial time algorithms known to solve this problem use complicated data structures. This paper proposes a very simple algorithm for computing all m shortest paths in a stage graph efficiently. The proposed algorithm does not use any complicated data structure and can be implemented in a straightforward way by using only array data structure. This problem appears as a sub-problem for planning risk reduced multiple k-legged trajectories for aerial vehicles.

Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky

AFIT Patents

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

Implementation Of Large Neural Networks Using Decomposition, Henry Selvaraj, H. Niewiadomski, P. Buciak, M. Pleban, Piotr Sapiecha, Tadeusz Luba, Venkatesan Muthukumar

Electrical & Computer Engineering Faculty Research

The article presents methods of dealing with huge data in the domain of neural networks. The decomposition of neural networks is introduced and its efficiency is proved by the authors’ experiments. The examinations of the effectiveness of argument reduction in the above filed, are presented. Authors indicate, that decomposition is capable of reducing the size and the complexity of the learned data, and thus it makes the learning process faster or, while dealing with large data, possible. According to the authors experiments, in some cases, argument reduction, makes the learning process harder.

Wavelet Domain Communication System (Wdcs): Packet-Based Wavelet Spectral Estimation And M-Ary Signaling, Marion Jay F. Lee

Theses and Dissertations

A recently proposed Wavelet Domain Communication System (WDCS) using transform domain processing demonstrated excellent interference avoidance capability under adverse environmental conditions. This work extends previous results by: 1) incorporating a wavelet packet decomposition technique, 2) demonstrating M-Ary signaling capability, and 3) providing increased adaptivity over a larger class of interference signals. The newly proposed packet-based WDCS is modeled and its performance characterized using MATLAB®. In addition, the WDCS response to two scenarios simulating Doppler effects and physical separation of transceivers are obtained. The fundamental metric for analysis and performance evaluation is bit error rate (P_b). Relative to …

Fingerprint Recognition Using Neural Networks, Eng Hoe Kennie Yeoh

Student Works (2000-2009)

Traditional methods of fingerprint verification uses either complicated feature detection algorithms that are not specific to each fingerprint, or compare two fingerprint images directly using image processing toots. The former involves very complicated calculations and tedious algorithms, and the latter tend to work poorly. In this paper it is described a new method which takes the middle ground. This paper studies the implementation of the Fast Fourier Transform and Artificial Neural Networks into the recognition of fingerprints. With tests conducted on the implementation of the Fourier Transform as a method of fingerprint feature extraction, the use of the Fourier Transform …

Joint Wavelet Transform Correlation With Separated Target And Reference Planes, Boon Yi Soon, Mohammad A. Karim, Russell C. Hardie, Mohammad S. Alam

Electrical and Computer Engineering Faculty Publications

In recent years, we realize the usefulness of feature extraction for optical correlator and hereby, we investigate the capability of Laplace operator in feature extraction of multiple targets. The first-order terms and the false alarm terms in the correlation output would be removed using electronic power spectrum subtraction technique. Most importantly, the entire magneto-optic SLM is completely utilized for displaying only targets in the input scene. A new cost efficient hardware implementation is proposed and aforementioned result of the proposed system is evaluated through computer simulation.

A Comparative Analysis Of Networks Of Workstations And Massively Parallel Processors For Signal Processing, David C. Gindhart

Theses and Dissertations

The traditional approach to parallel processing has been to use Massively Parallel Processors (MPPs). An alternative design is commercial-off-the-shelf (COTS) workstations connected to high-speed networks. These networks of workstations (NOWs) typically have faster processors, heterogeneous environments, and most importantly, offer a lower per node cost. This thesis compares the performance of MPPs and NOWs for the two-dimensional fast Fourier transform (2-D FFT). Three original, high-performance, portable 2-D FFTs have been implemented: the vector-radix, row-column and pipeline. The performance of these algorithms was measured on the Intel Paragon, IBM SP2 and the AFIT NOW, which consists of 6 Sun Ultra workstations …

Detection For A Statistically-Known, Time-Varying Dispersive Channel, David W. Matolak, S. G. Wilson

Faculty Publications

Detection for the statistically known channel (SKC) is aimed at obtaining good performance in situations where our statistical knowledge of a time-varying channel is good, and where other equalization/detection schemes are either too complex to implement, or their performance is limited due to the rapidity of channel fading, or where we are simply unable to perform channel estimation. By using a statistical characterization of the channel, we develop a new detector that performs maximum-likelihood sequence estimation (MLSE) (given the channel model) on blocks of N symbols. Both symbol-spaced and fractionally spaced samples are used, to obtain two different detectors, that …

Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan

Electrical & Computer Engineering Theses & Dissertations

Motivated by the fact that human speech perception is a bimodal process (auditory and visual), several researchers have designed and implemented automatic speech recognition (ASR) systems consisting of both audio and visual subsystems, and shown improved performance relative to traditional purely auditory systems. Several visual speech reading approaches have used deformable templates to model the shape of a speaker's lips. Deformable templates are models of image objects, which can be deformed by adjusting a set of parameters to match the object in some optimal way, as defined by a cost function. Using a single deformable lip model has disadvantages such …

Linda Jacobson Interview Virtual Reality Evangelist, Loretta L. Lange

SWITCH

In the interview with Linda Jacobson, a Virtual Reality (VR) artist, Jacobson discusses the current and future state of VR technology’s role in the politics of the body, social identity, self, gender, class, and race. This article discusses the fact that barriers to access exist for a more diverse set of artists across race, class, and gender to engage with VR technology and the need to evolve the development platform, so artists can implement their ideas in a low-cost way. The author discusses Jaron Lanier’s ideas about using VR to explore other identities based on a theatrical model where the …

A General Approach To Boolean Function Decomposition And Its Application In Fpgabased Synthesis, Tadeusz Luba, Henry Selvaraj

Electrical & Computer Engineering Faculty Research

An effective logic synthesis procedure based on parallel and serial decomposition of a Boolean function is presented in this paper. The decomposition, carried out as the very first step of the .synthesis process, is based on an original representation of the function by a set of r-partitions over the set of minterms. Two different decomposition strategies, namely serial and parallel, are exploited by striking a balance between the two ideas. The presented procedure can be applied to completely or incompletely specified, single- or multiple-output functions and is suitable for different types of FPGAs including XILINX, ACTEL and ALGOTRONIX devices. The …

Acoustic Correlates Of Vowel Perception As Determined From Synthesis Experiments With Multi-Tone Stimuli, Zhongjiang Zhang

Electrical & Computer Engineering Theses & Dissertations

An essential requirement of speech signal processing is to extract information (features or parameters) from the speech signal which encode the information carried by the signal. The objective of this thesis work was to examine and evaluate two feature sets as acoustic correlates for vowel perception. They are formants and DCTCs. Formants are the frequencies of spectral peaks of the speech signal. DCTCs are the Discrete Cosine Transform Coefficients of the magnitude spectrum and are thus features which encode the global spectral shape of speech signal.

There are different opinions regarding which feature set is a more accurate representation for …

Visual Speech Training Aid For The Deaf, Subhashri Venkat

Electrical & Computer Engineering Theses & Dissertations

A computer-based vowel articulation training aid has been developed. A "continuous" acoustic-phonetic transformation is performed to map speech parameters to a lower dimensionality display space. There are two possible approaches to this transformation problem. The transformation could be either linear or a combination nonlinear/linear. The nonlinear transformation is performed using a multi-layered feedforward neural network with linear output layers. Speech parameters are extracted either from an analog filter bank arrangement (band energies) or by a digital signal processing procedure (Discrete Cosine Transform Coefficients). The speech parameters obtained from both methods correspond to the spectral envelope of the speech signals. The …