Signal Processing Commons^™

Integrated Approach To Airborne Laser Communication, James A. Louthain

Theses and Dissertations

Lasers offer tremendous advantages over RF communication systems in bandwidth and security, due to their ultra-high frequency and narrow spatial beamwidth. Atmospheric turbulence causes severe received power variations and high bit error rates (BERs) in airborne laser communication. Airborne optical communication systems require special considerations in size, complexity, power, and weight. Conventional adaptive optics systems correct for the phase only and cannot correct for strong scintillation, but here the two transmission paths are separated sufficiently so that the strong scintillation is \averaged out" by incoherently summing up the two beams in the receiver. This requisite separation distance is derived for …

Hand-Held Flyback Driven Coaxial Dielectric Barrier Discharge: Development And Characterization, Victor J. Law, Vladimir Milosavljevic, Neil O’Connor, James F. Lalor, Steven Daniels

Articles

The development of a handheld single and triple chamber atmospheric pressure coaxial dielectric barrier discharge driven by Flyback circuitry for helium and argon discharges is described. The Flyback uses external metal-oxide-semiconductor field-effect transistor power switching technology and the transformer operates in the continuous current mode to convert a continuous dc power of 10–33 W to generate a 1.2–1.6 kV 3.5 μs pulse. An argon discharge breakdown voltage of ∼768 V is measured. With a 50 kHz, pulse repetition rate and an argon flow rate of 0.5–10 argon slm (slm denotes standard liters per minute), the electrical power density deposited in …

Performance Analysis Of Multicarrier Code Division Multiple Access (Mc-Cdma) Systems, Pravinkumar Patil

Morehead State Theses and Dissertations

A thesis presented to the faculty of the College of Science and Technology at Morehead State University in partial fulfillment of the requirements for the Degree of Master of Science by Pravinkumar Patil on August 11, 2008.

A Finite Queue Model Analysis Of Pmrc-Based Wireless Sensor Networks, Qiaoqin Li, Mei Yang, Hongyan Wang, Yingtao Jiang, Jiazhi Zeng

Electrical & Computer Engineering Faculty Research

In our previous work, a highly scalable and fault- tolerant network architecture, the Progressive Multi-hop Rotational Clustered (PMRC) structure, is proposed for constructing large-scale wireless sensor networks. Further, the overlapped scheme is proposed to solve the bottleneck problem in PMRC-based sensor networks. As buffer space is often scarce in sensor nodes, in this paper, we focus on studying the queuing performance of cluster heads in PMRC-based sensor networks. We develop a finite queuing model to analyze the queuing performance of cluster heads for both non-overlapped and overlapped PMRC-based sensor network. The average queue length and average queue delay of cluster …

Perceptually Motivated Wavelet Packet Transform For Bioacoustic Signal Enhancement, Yao Ren, Michael T. Johnson, Jidong Tao

Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations

A significant and often unavoidable problem in bioacoustic signal processing is the presence of background noise due to an adverse recording environment. This paper proposes a new bioacoustic signal enhancement technique which can be used on a wide range of species. The technique is based on a perceptually scaled wavelet packet decomposition using a species-specific Greenwood scale function. Spectral estimation techniques, similar to those used for human speech enhancement, are used for estimation of clean signal wavelet coefficients under an additive noise model. The new approach is compared to several other techniques, including basic bandpass filtering as well as classical …

The 5 Ghz Airport Surface Area Channel: Part Ii, Measurement And Modeling Results For Small Airports, Indranil Sen, David W. Matolak

Faculty Publications

This paper describes results from a channel measurement campaign performed at several small airports in the U.S. in the 5-GHz band. This paper is a companion to another paper, which describes channel models for large airports. We classify the small airport surface channel into three propagation regions based upon different delay dispersion conditions. The channel characteristics of these regions in the delay and frequency domains are discussed with examples. We provide empirical stochastic channel models (of different bandwidths) to accurately represent the channel on the airport surface area for all propagation regions. The models are provided in the form of …

A Wide Area Bipolar Cascade Resonant Cavity Light Emitting Diode For A Hybrid Range-Intensity, Reginald J. Turner

Theses and Dissertations

This dissertation focused on the development of an illuminator for the HRIS. This illuminator enables faster image rendering and reduces the potential of errors in return signal data, that could be generated from extremely rough terrain. Four major achievements resulted from this work, which advance the field of 3-D image acquisition. The first is that the TJ is an effective current spreading layer for LEDs with mesa width up to 140 micrometers and current densities of approximately 1 x 10⁶ Amp/square centimeter. The TJ allows fabrication of an efficient illuminator, with required geometry for the HRIS to operate as …

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, …

Statistical Methods For Image Registration And Denoising, Matthew D. Sambora

Theses and Dissertations

This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing a novel method that exploits local correlations to improve the performance of projection-based image registration algorithms. The dissertation also extends the bounds on image registration performance for both projection-based and full-frame image registration algorithms and extends the Barankin bound from the one-dimensional case to the problem of two-dimensional image registration. It is demonstrated that in some instances, the Cramer-Rao lower bound is an overly-optimistic predictor of image registration performance and that under some conditions, the …

A Real-Time Framework For Video Time And Pitch Scale Modification, Ivan Damnjanovic, Dan Barry, David Dorran, Josh Reiss

Conference papers

A framework is presented which addresses the issues related to the real-time implementation of synchronised video and audio time-scale and pitch-scale modification algorithms. It allows for seamless real-time transition between continually varying, independent time-scale and pitch-scale parameters arising as a result of manual or automatic intervention. We illuminate the problems which arise in a real-time context as well as provide novel solutions to prevent artefacts, minimise latency, and improve synchronisation. The time and pitch scaling approach is based on a modified phase vocoder with optional phase locking and an integrated transient detector which enables high quality transient preservation in real-time. …

Vehicle-Vehicle Channel Models For The 5 Ghz Band, Indranil Sen, David W. Matolak

Faculty Publications

In this paper, we describe the results of a channel measurement and modeling campaign for the vehicle-to-vehicle (V2V) channel in the 5-GHz band. We describe measurements and results for delay spread, amplitude statistics, and correlations for multiple V2V environments. We also discuss considerations used in developing statistical channel models for these environments and provide some sample results. Several statistical channel models are presented, and using simulation results, we elucidate tradeoffs between model implementation complexity and fidelity. The channel models presented should be useful for system designers in future V2V communication systems.

Channel Modeling For Vehicle-To-Vehicle Communications, David W. Matolak

Faculty Publications

Physical layer channel modeling is critical for design and performance evaluation at multiple layers of the communications protocol stack. In this article we describe and provide results for modeling vehicle-to-vehicle (V2V) wireless channels. V2V settings produce some unique conditions, and due to these conditions, V2V channels often exhibit greater dynamics than many conventional channels and, in addition, can also exhibit more severe fading. Thus, new channel models are needed to characterize this setting in order to evaluate contending transmission schemes and aid in V2V communication system design. A brief review of key statistical channel parameters is provided. Then both analytical …

Spectrally Shaped Generalized Mc-Ds-Cdma With Dual Band Combining For Increased Diversity, Wenhui Xiong, David W. Matolak

Faculty Publications

A new multicarrier spread spectrum modulation scheme is proposed in this paper. This scheme uses sinusoidal chip waveforms to shape the spectrum of each subcarrier of a multicarrier direct sequence spread spectrum (DS-SS) signal. As a result, each subcarrier has two distinct spectral lobes, one a lower sideband (LSB) and the other an upper sideband (USB). By properly selecting the parameters of the sinusoidal chip waveforms, the two sideband signals can be made to undergo independent fading in a dispersive fading channel. These two independently-faded sideband signals, when combined at the receiver, provide diversity gain to the system. Our analysis …

Real-Time Plasma Controlled Chemistry In A Two-Frequency, Confined Plasma Etcher, Vladimir Milosavljevic, Albert R. Ellingboe, Cezar Gaman, John V. Ringwood

Articles

The physics issues of developing model-based control of plasma etching are presented. A novel methodology for incorporating real-time model-based control of plasma processing systems is developed. The methodology is developed for control of two dependent variables (ion flux and chemical densities) by two independent controls (27 MHz power and O2flow). A phenomenological physics model of the nonlinear coupling between the independent controls and the dependent variables of the plasma is presented. By using a design of experiment, the functional dependencies of the response surface are determined. In conjunction with the physical model, the dependencies are used to deconvolve the sensor …

Multi-Reference Frame Image Registration For Rotation, Translation, And Scale, Christopher S. Costello

Theses and Dissertations

This thesis investigates applications of multi-reference frame image registration for image sets with various translation, rotation, and scale combinations. It focuses on registration accuracy improvement over traditional pairwise registration, and also compares the quality of scene estimation from frame averaging. Three experiments are developed which use cross-correlation to estimate translation, the Radon transform to estimate translation and rotation, and the Fourier-Mellin transform to estimate translation, rotation, and scale. Results from applying multi-reference frame registration in these experiments show distinct improvements in both registration accuracy and quality of frame averaging compared to single-reference frame registration. Furthermore, it is shown that the …

Acoustic Model Adaptation For Ortolan Bunting (Emberiza Hortulana L.) Song-Type Classification, Jidong Tao, Michael T. Johnson, Tomasz S. Osiejuk

Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations

Automatic systems for vocalization classification often require fairly large amounts of data on which to train models. However, animal vocalization data collection and transcription is a difficult and time-consuming task, so that it is expensive to create large data sets. One natural solution to this problem is the use of acoustic adaptation methods. Such methods, common in human speech recognition systems, create initial models trained on speaker independent data, then use small amounts of adaptation data to build individual-specific models. Since, as in human speech, individual vocal variability is a significant source of variation in bioacoustic data, acoustic model adaptation …

An Improved Snr Estimator For Speech Enhancement, Yao Ren, Michael T. Johnson

Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations

In this paper, we propose an MMSE a priori SNR estimator for speech enhancement. This estimator has similar benefits to the well-known decision-directed approach, but does not require an ad-hoc weighting factor to balance the past a priori SNR and current ML SNR estimate with smoothing across frames. Performance is evaluated in terms of estimation error and segmental SNR using the standard logSTSA speech enhancement method. Experimental results show that, in contrast with the decision-directed estimator and ML estimator, the proposed SNR estimator can help enhancement algorithms preserve more weak speech information and efficiently suppress musical noise.

Multi-Class Classification Fusion Using Boosting For Identifying Steganography Methods, Benjamin M. Rodriguez, Gilbert L. Peterson

Faculty Publications

No abstract provided.

Digital Signal Processing Leveraged For Intrusion Detection, Theodore J. Erickson

Theses and Dissertations

This thesis describes the development and evaluation of a novel system called the Network Attack Characterization Tool (NACT). The NACT employs digital signal processing to detect network intrusions, by exploiting the Lomb-Scargle periodogram method to obtain a spectrum for sampled network traffic. The Lomb-Scargle method for generating a periodogram allows for the processing of unevenly sampled network data. This method for determining a periodogram has not yet been used for intrusion detection. The spectrum is examined to determine if features exist above a significance level chosen by the user. These features are considered an attack, triggering an alarm. Two traffic …

Hyperspectral-Augmented Target Tracking, Neil A. Soliman

Theses and Dissertations

With the global war on terrorism, the nature of military warfare has changed significantly. The United States Air Force is at the forefront of research and development in the field of intelligence, surveillance, and reconnaissance that provides American forces on the ground and in the air with the capability to seek, monitor, and destroy mobile terrorist targets in hostile territory. One such capability recognizes and persistently tracks multiple moving vehicles in complex, highly ambiguous urban environments. The thesis investigates the feasibility of augmenting a multiple-target tracking system with hyperspectral imagery. The research effort evaluates hyperspectral data classification using fuzzy c-means …

Signal Processing Design Of Low Probability Of Intercept Waveforms, Nathaniel C. Liefer

Theses and Dissertations

This thesis investigates a modification to Differential Phase Shift Keyed (DPSK) modulation to create a Low Probability of Interception/Exploitation (LPI/LPE) communications signal. A pseudorandom timing offset is applied to each symbol in the communications stream to intentionally create intersymbol interference (ISI) that hinders accurate symbol estimation and bit sequence recovery by a non-cooperative receiver. Two cooperative receiver strategies are proposed to mitigate the ISI due to symbol timing offset: a modified minimum Mean Square Error (MMSE) equalization algorithm and a multiplexed bank of equalizer filters determined by an adaptive Least Mean Square (LMS) algorithm. Both cooperative receivers require some knowledge …

Joint Image And Pupil Plane Reconstruction Algorithm Based On Bayesian Techniques, James D. Phillips

Theses and Dissertations

The focus of this research was to develop an joint pupil and focal plane image recovery algorithm for use with coherent LADAR systems. The benefits of such a system would include increased resolution with little or no increase in system weight and volume as well as allowing for operation in the absence of natural light since the target of interest would be actively illuminated. Since a pupil plane collection aperture can be conformal, such a system would also potentially allow for the formation of large synthetic apertures. The system is demonstrated to be robust and in all but extreme cases …

Color Filter Array Image Analysis For Joint Denoising And Demosaicking, Keigo Hirakawa

Electrical and Computer Engineering Faculty Publications

Noise is among the worst artifacts that affect the perceptual quality of the output from a digital camera. While cost-effective and popular, single-sensor solutions to camera architectures are not adept at noise suppression. In this scheme, data are typically obtained via a spatial subsampling procedure implemented as a color filter array (CFA), a physical construction whereby each pixel location measures the intensity of the light corresponding to only a single color. Aside from undersampling, observations made under noisy conditions typically deteriorate the estimates of the full-color image in the reconstruction process commonly referred to as demosaicking or CFA interpolation in …

The Annotation Of Traditional Irish Dance Music Using Matt2 And Tansey, Bryan Duggan, Brendan O'Shea, Mikel Gainza, Padraig Cunningham

Conference papers

Current estimates put the canon of traditional Irish dance tunes at least 7,000 compositions. Given this diversity, a common problem faced by musicians and ethnomusicologists is identifying tunes from recordings. This is evident even in the number of commercial recordings whose title is gan aimn (without name). This work attempts to solve this problem by developing a Content Based Music Information Retrieval (CBMIR) System adapted to the characteristics of traditional Irish music. A system is presented called MATT2 (Machine Annotation of Traditional Tunes) whose primary goal is to annotate recordings of traditional Irish dance music with useful meta-data including tune …

Linear Prediction: The Problem, Its Solution And Application To Speech, Alan O'Cinneide, David Dorran, Mikel Gainza

Conference papers

Linear prediction is a signal processing technique that is used extensively in the analysis of speech signals and, as it is so heavily referred to in speech processing literature, a certain level of familiarity with the topic is typically required by all speech processing engineers. This paper aims to provide a well-rounded introduction to linear prediction, and so doing, facilitate the understanding of the technique. Linear prediction and its mathematical derivation will be described, with a specific focus on applying the technique to speech signals. It is noted, however, that although progress in linear prediction has been driven primarily by …

A Surface Inspection Machine Vision System That Includes Fractal Texture Analysis, Jonathan Blackledge, Dmitry Dubovitskiy

Articles

The detection, recognition and classification of features in a digital image is an important component of quality control systems in production and process engineering and industrial systems monitoring, in general. In this paper, a new pattern recognition system is presented that has been designed for the specific task of monitoring the quality of sheet-steel production in a rolling mill. The system is based on using both the Euclidean and Fractal geometric properties of an imaged object to develop training data that is used in conjunction with a supervised learning procedure based on the application of a fuzzy inference engine. Thus, …

Object Detection And Classification With Applications To Skin Cancer Screening, Jonathan Blackledge, Dmitryi Dubovitskiy

Articles

This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

The principal issues associated with object recognition are presented which includes two novel fast segmentation algorithms for which C++ code is provided. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and …

Drop Photometer Design., Kevin Tiernan

Doctoral

The tensiograph drop analyser, operating in the mode of ultraviolet-visual absorption photometer, was re-engineered to improve measurement accuracy. As well as instrumentation re-design, the other objective of the research was to analyse tensiograph signals to explore how their features are defined by drop properties. Using fibre optic technology, the tensiograph emits a light beam into a growing pendant drop whereupon it undergoes a number of internal reflections. A portion of the reflected light energy is coupled to a photodiode producing a proportional current that is electronically processed and transferred to a computer for analysis. The signal produced, known as the …

Analysis Of Financial Data Using Non-Negative Matrix Factorization, Ruairí De Fréin, Konstantinos Drakakis, Scott Rickard, Andrzej Cichocki

Articles

We apply Non-negative Matrix Factorization (NMF) to the prob-lem of identifying underlying trends in stock market data. NMF is arecent and very successful tool for data analysis including image andaudio processing; we use it here to decompose a mixture a data, thedaily closing prices of the 30 stocks which make up the Dow Jones In-dustrial Average, into its constitute parts, the underlying trends which govern the financial marketplace. We demonstrate how to impose ap-propriate sparsity and smoothness constraints on the components of thedecomposition. Also, we describe how the method clusters stocks to-gether in performance-based groupings which can be used for …

Improvement Of Prony's Method Of System Identification Vianonlinear Parameter Transformation, C. Wu

Journal of the Arkansas Academy of Science

This paper presents an approach to improve Prony’s method of identifying a linear time-invariant system. The method is based on a nonlinear transformation of parameters, which leads to data averaging. The method yields better results than a direct application of the least squares approach to Prony’s method. A numerical example is given to demonstrate the improvement attained by the new algorithm. Signals are assumed to be contaminated by zero-mean Gaussian white noise.