Signal Processing Commons^™

Effects Of Channel Mismatches On Beamforming And Signal Detection, Christopher I. Allen

Theses and Dissertations

Tuner gain measurements of a multichannel receiver are reported. A linear regression model is used to characterize the gain, as a function of channel number, tuner set-on frequency, and intermediate frequency. Residual errors of this model are characterized by a t distribution. Very strong autocorrelation of tuner gain at various frequencies is noted. Tuner performance from one channel to the next is diverse; several defects at specific frequencies are noted. The Wilcoxon signed rank test is used to test normality of tuner gain among devices; normality is rejected. Antenna directivity and phase pattern measurements are also reported. An antenna element …

A Robust Method To Detect Concealed Weapons, Anand Gone

Electrical & Computer Engineering Theses & Dissertations

Concealed weapons detection is a large problem that is faced by the Police Department nowadays. There are many disasters caused by poor detection of the weapons. Since public safety is at risk there is a need to design an efficient detector that can detect the weapons hidden under the clothing. This thesis presents a novel method for detecting concealed weapons under clothing using image processing techniques. In this thesis IR imagery is used to capture an image which works on the principle of law of black body radiation. Image thresholding is performed on the captured data using Sauvola's adaptive thresholding …

Frequency Diversity For Improving Synthetic Aperture Radar Imaging, Jawad L. Farooq

Theses and Dissertations

In this work, a novel theoretical framework is presented for using recent advances in frequency diversity arrays (FDAs). Unlike a conventional array, the FDA simultaneously transmits a unique frequency from each element in the array. As a result, special time and space properties of the radiation pattern are exploited to improve cross-range resolution. The idealized FDA radiation pattern is compared with and validated against a full-wave electromagnetic solver, and it is shown that the conventional array is a special case of the FDA. A new signal model, based on the FDA, is used to simulate SAR imagery of ideal point …

Bit-Error-Rate-Minimizing Channel Shortening Using Post-Feq Diversity Combining And A Genetic Algorithm, Gokhan Altin

Theses and Dissertations

In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter …

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …

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 …

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 …

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 …

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 …

Reed-Solomon Codes Construction & Decoding, Samuel J. Parsons

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.

Methods And System For Equalizing Data In Multicarrier Receiver Systems, Richard K. Martin, Jaiganesh Balakrishnan, Wonzoo Chung, C. Richard Johnson

AFIT Patents

A method for equalizing data and systems utilizing the method. The method of this invention for equalizing (by shortening the channel response) data includes minimizing a function of the data and a number of equalizer characteristic parameters, where the function utilizes cyclic differences of equalized data. Updated equalizer characteristic parameters are then obtained from the minimization and an initial set of equalizer characteristic parameters. Finally, the received data is processed utilizing the equalizer defined by the minimization. The method of this invention can be implemented in an equalizer and the equalizer of this invention may be included in a system …

Steganalysis Feature Improvement Using Expectation Maximization, Benjamin M. Rodriguez, Gilbert L. Peterson, Sos S. Agaian

Faculty Publications

No abstract provided.

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, …

Apparatus And Method For Using Adaptive Algorithms To Exploit Sparsity In Target Weight Vectors In An Adaptive Channel Equalizer, Richard K. Martin, Robert C. Williamson, William A. Sethares

AFIT Patents

An apparatus and method is disclosed for using adaptive algorithms to exploit sparsity in target weight vectors in an adaptive channel equalizer. An adaptive algorithm comprises a selected value of a prior and a selected value of a cost function. The present invention comprises algorithms adapted for calculating adaptive equalizer coefficients for sparse transmission channels. The present invention provides sparse algorithms in the form of a Sparse Least Mean Squares (LMS) algorithm and a Sparse Constant Modulus Algorithm (CMA) and a Sparse Decision Directed (DD) algorithm.

Multiple Masks-Based Pixel Comparison Steganalysis Method For Mobile Imaging, Sos S. Agaian, Gilbert L. Peterson, Benjamin M. Rodriguez

Faculty Publications

No abstract provided.

Multiframe Shift Estimation, Stephen A. Bruckart

Theses and Dissertations

The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …

Verification Of A Decision Level Fusion Algorithm Using A Proven Atr System And Measured Sar Data, James Douglas Thompson

Theses and Dissertations

Decision level fusion (DLF) algorithms combine outputs of multiple single sensors to make one confident declaration of a target. This research compares performance results of a DLF algorithm using measured data and a proven ATR system with results from simulated data and a modeled ATR system. This comparison indicates that DLF offers significant performance improvements over single sensor looks. However, results based on simulated data and a modeled ATR are slightly optimistic and overestimate results from measured data and a proven ATR system by nearly 10% over all targets tested.

Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham

Theses and Dissertations

The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …

A Fast And Simple Algorithm For Computing M Shortest Paths In Stage 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.

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.

A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan

Electrical & Computer Engineering Theses & Dissertations

Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …

Inquisitive Pattern Recognition, Amy L. Magnus

Theses and Dissertations

The Department of Defense and the Department of the Air Force have funded automatic target recognition for several decades with varied success. The foundation of automatic target recognition is based upon pattern recognition. In this work, we present new pattern recognition concepts specifically in the area of classification and propose new techniques that will allow one to determine when a classifier is being arrogant. Clearly arrogance in classification is an undesirable attribute. A human is being arrogant when their expressed conviction in a decision overstates their actual experience in making similar decisions. Likewise given an input feature vector, we say …

Yet Another Algorithm For Pitch Tracking (Yaapt), Kavita Kasi

Electrical & Computer Engineering Theses & Dissertations

This thesis presents a pitch detection algorithm that is extremely robust for both high quality and telephone speech. The kernel method for this algorithm is the Normalized Cross Correlation (NCCF) reported by David Talkin [16]. Major innovations include: processing of the original acoustic signal and a nonlinearly processed version of the signal to partially restore very weak F0 components; intelligent peak picking to select multiple F0 candidates and assign merit factors; and, incorporation of highly robust pitch contours obtained from smoothed versions of low frequency portions of spectrograms. Dynamic programming is used to find the ''best" pitch track among all …

Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra

Theses and Dissertations

The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …

Mobile Home Security With Gprs, Duy Nguyen

Theses : Honours

This thesis presents the results of an honours project on the development of a security system for use on mobile devices. Mobile Home Security (MHS) is a prototype system that aimed to fully investigate a potential use of the wireless high-speed technology General Packet Radio Service (GPRS) in transmitting video from a static location. This thesis Mobile Home Security with GPRS describes in detail the design and developmental stages for the system. The research focused on the sending of video from a security capture device over a high speed radio network. The first stage of the research involved the design …

Aurora Working Group: Dsr Front End Lvcsr Evaluation — Baseline Recognition System Description, Naveen Parihar, Joseph Picone

Publications

In this document we describe the features of the baseline system to be used in the Distributed Speech Recognition (DSR) front end large vocabulary continuous speech recognition (LVCSR) evaluations being conducted by the Aurora Working Group of the European Telecommunications Standards Institute (ETSI). The objective of these evaluations is to determine the robustness of different front ends for use in client/server type telecommunications applications. As such, our experiments are designed to test the following focus conditions on the DARPA Wall Street Journal (WSJ0) corpus using a 5000-word closed-loop vocabulary and a bigram language model:

1. Additive Noise: six noise conditions …

An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga

Theses and Dissertations

Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts, automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms, but they have not been tested on a common set of images, and there are no standard test methods. This thesis evaluates four SAR image segmentation algorithms by running them on a common set of data and objectively comparing them to each other and to human segmentors. This objective comparison uses a multi-metric a approach with a set of …

Video Compression Using Wavelets And Hierarchical Motion Estimation, Andrew Peter Byrne

Theses : Honours

This thesis investigates the benefits and the significant compression that can be obtained from data that has been decomposed using a wavelet transform. A video compression algorithm was developed that employs the wavelet transform and a hierarchical motion estimation algorithm which itself utilises benefits of the wavelet transform. Using MATLAB, a popular software tool for matrix based computation and analysis, several functions were developed which together formed the video compression algorithm. A variety of tests were conducted on a sample video sequence to ascertain the strengths and weaknesses of the techniques employed. The results, although not the same as the …

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 …