Signal Processing Commons^™

The Interacting Multiple Models Algorithm With State-Dependent Value Assignment, Rastin Rastgoufard

LSU New Orleans Theses and Dissertations

The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game's player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. …

Converting Three-Component To Four-Component Image (2012), Ronald S. Cok, Michael E. Miller

AFIT Patents

A method of converting a three-or-more-color-component image input signal to an image output signal includes acquiring an input signal having a plurality of pixel signals, each pixel signal having three, or more, color components; determining a residual difference for each color component of each pixel signal; determining a limit value of the residual differences; calculating a common scale factor for each of the color components based upon the limit value; and applying the common scale factor to the image input signal to produce the image output signal.

Multi-Circle Detections For An Automatic Medical Diagnosis System, Dingran Lu

Master's Theses

Real-time multi-circle detection has been a challenging problem in the field of biomedical image processing, due to the variable sizes and non-ideal shapes of cells in microscopic images. In this study, two new multi-circle detection algorithms are developed to facilitate an automatic bladder cancer diagnosis system: one is a modified circular Hough Transform algorithm integrated with edge gradient information; and the other one is a stochastic search approach based on real valued artificial immune systems. Computer simulation results show both algorithms outperform traditional methods such as the Hough Transform and the geometric feature based method, in terms of both precision …

Vision-Based Human Action Recognition: A Sparse Representation Perspective, Zhe Zhang

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The objective of vision-based human action recognition is to label the video sequence with its corresponding action category. In this thesis, the human action recognition problem is solved from a novel sparse representation perspective. First, spatial-temporal interest points are extracted in the video sequences. Then, a cuboid is extracted centered at each spatial-temporal interest point. The histogram of oriented gradients (HOG) and histogram of flow (HOF) descriptors for each cuboid are computed and concatenated into a one-dimensional vector. The K-Means clustering algorithm is used to cluster these cuboid feature vectors into a few visual codewords. Finally, each action instance is …

The Presence Of Regional Accents In Electrolarynx Speech And The Resultant Effect On Overall Intelligibility., Brian Madden, Eugene Coyle

Conference Papers

During voiced speech, the larynx provides quasi-periodic acoustic excitation of the vocal tract. In most electrolarynxes, mechanical vibrations are produced by a linear electromechanical actuator, the armature of which percusses against a metal or plastic plate at a frequency within the range of glottal excitation. In this paper, a phonological analysis of a section of results from an online perceptual intelligibility test was performed which compared speech produced using a novel hands-free electrolarynx and a commercially available electrolarynx. A portion of the test consisted of a closed-set format containing a selection of four sets of four random CVC audio samples …

Robot X, Alan Truong, Alex Haag

Computer Engineering

The following report outlines the design decisions behind Robot X for the 2012 Cal Poly Roborodentia competition held annually during Open House. This investigation includes detailed overview of Robot X's sensory system, driving system, conveyor belt system, and can compartment system. In addition, basic hardware and software design are explored.

Ofdm-Based Signal Exploitation Using Quadrature Mirror Filter Bank (Qmfb) Processing, Felipe E. Garrido

Theses and Dissertations

By performing QMFB processing with a given signal it is possible to obtain Frequency-Time (F-T) outputs that represent signal features such as bandwidth (W), center frequency (fc), signal duration (Ts), modulation type (AM, FM, BPSK, QAM, etc), frequency content and time allocation. Because of its unique structure, two widely used signals based on Orthogonal Frequency Division Multiplexing (OFDM) were chosen as signals of interest for demonstration. The general implementation of the QMFB process is described along with the basic structure of OFDM signals related to the physical layer perspective of 802.11a Wi-Fi and 802.16e WiMAX frame structures are described. The …

Binary Classification Of An Unknown Object Through Atmospheric Turbulence Using A Polarimetric Blind-Deconvolution Algorithm Augmented With Adaptive Degree Of Linear Polarization Priors, Mu J. Kim

Theses and Dissertations

This research develops an enhanced material-classification algorithm to discriminate between metals and dielectrics using passive polarimetric imagery degraded by atmospheric turbulence. To improve the performance of the existing technique for near-normal collection geometries, the proposed algorithm adaptively updates the degree of linear polarization (DoLP) priors as more information becomes available about the scene. Three adaptive approaches are presented. The higher-order super-Gaussian method fits the distribution of DoLP estimates with a sum of two super-Gaussian functions to update the priors. The Gaussian method computes the classification threshold value, from which the priors are updated, by fitting the distribution of DoLP estimates …

Ladar Range Image Interpolation Exploiting Pulse Width Expansion, Jeramy W. Motes

Theses and Dissertations

Laser Detection and Ranging (LADAR) systems produce both a range image and an intensity image by measuring the intensity of light reflected off a surface target. When the transmitted LADAR pulse strikes a sloped surface, the returned pulse is expanded temporally. This characteristic of the reflected laser pulse enables the possibility of estimating the gradient of a surface. This study estimates the gradient of the surface of an object from a modeled LADAR return pulse that includes accurate probabilistic noise models. The range and surface gradient estimations are incorporated into a novel interpolator that facilitates an effective three dimensional (3D) …

Passive Multistatic Radar Imaging Using An Ofdm Based Signal Of Opportunity, Matthew B. P. Rapson

Theses and Dissertations

This paper demonstrates a proof of concept in using an OFDM-based signal of opportunity for SAR imaging purposes within a passive, multistatic radar construct. Two signal processing methods have been proposed to create phase history data. The same methods are applied in both a simulated software model and an experimental data collection environment to produce simulated SAR images using the CBP imaging algorithm. The images generated from both the experimental and simulated data were observed to be consistent with each other and with expectations in terms of resolution. Coherent addition of the images results in improved image resolution due to …

Simultaneous Range-Velocity Processing And Snr Analysis Of Afit's Random Noise Radar, T. Joel Thorson

Theses and Dissertations

This paper presents two research objectives aimed at advancing the AFIT RNR signal processing algorithm and modeling capability toward the overarching goal of performing collision avoidance on an autonomous vehicle. In both research efforts, analytical, simulated, and measured results are provided and used to draw research conclusions. The first research effort is aimed at reducing the memory required for 2D processing in the time domain in order to distribute the processing algorithm across hundreds of processors on a GPU. Distributed processing reduces the overall 2D processing time and the feasibility of a near real-time implementation is studied. The second effort …

An Inquiry: Effectiveness Of The Complex Empirical Mode Decomposition Method, The Hilbert-Huang Transform, And The Fast-Fourier Transform For Analysis Of Dynamic Objects, Kristen L. Wallis

Theses and Dissertations

A review of current signal analysis tools show that new techniques are required for an enhanced fidelity or data integrity. Recently, the Hilbert-Huang transform (HHT) and its inherent property, the Empirical Mode Decomposition (EMD) technique, have been formerly investigated. The technique of Complex EMD (CEMD) was also explored. The scope of this work was to assess the CEMD technique as an innovative analysis tool. Subsequent to this, comparisons between applications of the Hilbert transform (HT) and the Fast-Fourier transform (FFT) were analyzed. MATLAB was implemented to model signal decomposition and the execution of mathematical transforms for generating results. The CEMD …

Low Cost, Low Complexity Sensor Design For Non-Cooperative Geolocation Via Received Signal Strength, Michael S. Butler

Theses and Dissertations

Obtaining accurate non-cooperative geolocation is vital for persistent surveillance of a hostile emitter. Current research for developing a small, cheap and energy efficient sensor network for non-cooperative geolocation measurements via received signal strength (RSS) is limited. Most existing work focuses on simulating a non-cooperative network (NN) and in doing so, simulated models often ignore localization errors caused from the hardware processing raw RSS data and often model environment-dependent errors as random. By comparing real-time measured non-cooperative geolocation data to a simulated system a more accurate model can be developed. This thesis discusses the development and performance of a small, low …

Spectral Detection Of Human Skin In Vis-Swir Hyperspectral Imagery Without Radiometric Calibration, Andrew P. Beisley

Theses and Dissertations

Many spectral detection algorithms require precise ground truth measurements that are hand-selected in the image to apply radiometric calibration, converting image pixels into estimated reflectance vectors. That process is impractical for mobile, real-time hyperspectral target detection systems, which cannot empirically derive a pixel-to-reflectance relationship from objects in the image. Implementing automatic target recognition on high-speed snapshot hyperspectral cameras requires the ability to spectrally detect targets without performing radiometric calibration. This thesis demonstrates human skin detection on hyperspectral data collected at a high frame rate without using calibration panels, even as the illumination in the scene changes. Compared to an established …

Dismount Threat Recognition Through Automatic Pose Identification, Andrew M. Freeman

Theses and Dissertations

The U.S. military has an increased need to rapidly identify nonconventional adversaries. Dismount detection systems are being developed to provide more information on and identify any potential threats. Current work in this area utilizes multispectral imagery to exploit the spectral properties of exposed skin and clothing. These methods are useful in the location and tracking of dismounts, but they do not directly discern a dismount's level of threat. Analyzing the actions that precede hostile events yields information about how the event occurred and uncovers warning signs that are useful in the prediction and prevention of future events. A dismount's posturing, …

Local Histograms For Per-Pixel Classification, Melody L. Massar

Theses and Dissertations

We introduce a rigorous mathematical theory for the analysis of local histograms, and study how they interact with textures that can be modeled as occlusions of simpler components. We first show how local histograms can be computed as a system of convolutions and discuss some basic local histogram properties. We then introduce a probabilistic, occlusion-based model for textures and formally demonstrate that local histogram transforms are natural tools for analyzing the textures produced by our model. Next, we characterize all nonlinear transforms which satisfy the three key properties of local histograms and consider the appropriateness of local histogram features in …

Power Spectral Densities Of Baseband Signals In Epc Class-1 Gen-2 Uhf Rfid Systems, Robert H. Morelos-Zaragoza

Faculty Publications

The power spectral densities (PSD) of baseband signals in EPC Class-1 Gen-2 UHF RFID systems are shown. PSD are obtained using Matlab as the Fourier transform (via the FFT algorithm) of the autocorrelation function of random pulse sequences. The PSD of PIE, FM0 and Miller subcarrier for M=2, 4 and 8 are shown for both unipolar (for 100% ASK or OOK modulation) and polar (PSK modulation) waveforms.

2012 First Annual State Of Resnet Report

ACUTA: Other Publications

In This Issue

Introduction

Methodology

Executive Summary

Structure of the ResNet

Network Infrastructure

Staffing, Service & Support

Fees & Budgets

On Inpainting The Adress Algorithm, Derry Fitzgerald, Dan Barry

Conference papers

The Adress algorithm has been demonstrated to be capable of separating sound sources from instantaneous linear mixtures, provided that the sources have a unique pan position in the stereo field. However, a shortcoming of the Adress algorithm is that all time-frequency bins outside of the chosen azimuth range are set to zero, resulting in audible artifacts in the resynthesised sound. Here we show that an inpainting algorithm based on NMF is capable of estimating these missing values and improves on the results obtained using Adress only.

On The Use Of Masking Filters In Sound Source Separation, Derry Fitzgerald, Rajesh Jaiswal

Conference papers

Many sound source separation algorithms, such as NMF and related approaches, disregard phase information and operate only on magnitude or power spectrograms. In this context, generalised Wiener filters have been widely used to generate masks which are applied to the original complex-valued spectrogram before inversion to the time domain, as these masks have been shown to give good results. However, these masks may not be optimal from a perceptual point of view. To this end, we propose new families of masks and compare their performance to generalised Wiener filter masks using three different factorisation-based separation algorithms. Further, to-date no analysis …