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Articles 31 - 45 of 45
Full-Text Articles in Signal Processing
A Fast And Simple Algorithm For Computing M-Shortest Paths In State Graph, M. Sherwood, Laxmi P. Gewali, Henry Selvaraj, Venkatesan Muthukumar
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.
Yet Another Algorithm For Pitch Tracking (Yaapt), Kavita Kasi
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
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 …
An Objective Evaluation Of Four Sar Image Segmentation Algorithms, Jason B. Gregga
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
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 …
Vhdl Design And Simulation For Embedded Zerotree Wavelet Quantisation, Hung Huynh
Vhdl Design And Simulation For Embedded Zerotree Wavelet Quantisation, Hung Huynh
Theses : Honours
This thesis discusses a highly effective still image compression algorithm – The Embedded Zerotree Wavelets coding technique, as it is called. This technique is simple but achieves a remarkable result. The image is wavelet-transformed, symbolically coded and successive quantised, therefore the compression and transmission/storage saving can be achieved by utilising the structure of zerotree. The algorithm was first proposed by Jerome M. Shapiro in 1993, however to minimise the memory usage and speeding up the EZW processor, a Depth First Search method is used to transverse across the image rather than Breadth First Search method as initially discussed in Shapiro's …
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Theses and Dissertations
Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …
Building Lms Adaptive Filters With Register-Based Fpgas, Li Ding
Building Lms Adaptive Filters With Register-Based Fpgas, Li Ding
Electrical & Computer Engineering Theses & Dissertations
In this thesis, an 8-bit least mean squares (LMS) adaptive digital filter with 16 coefficients is implemented on a single FPGA, using the MaxPlus+2 design environment. The system is constructed as a hierarchical structure, using four different levels of design hierarchy. Subdesigns at each level of the hierarchy project are complied, fitted and simulated to test and verify their functional correctness. The complete system is tested and verified by checking the MaxPlus+2 simulator results against fixed-point integer arithmetic simulations written in Matlab. The resulting adaptive filter is subsequently mapped to the Alters FLEX I OK20TC144-3 device, resulting in a 14,500 …
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Theses and Dissertations
Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …
Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan
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 …
Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su
Electrical & Computer Engineering Theses & Dissertations
An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.
In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.
The semi-continuous HMM is a class of models …
Formant Estimation From Dctc's Using A Feedforward Neural Network, Shubhangi U. Kelkar
Formant Estimation From Dctc's Using A Feedforward Neural Network, Shubhangi U. Kelkar
Electrical & Computer Engineering Theses & Dissertations
Formants are the natural frequencies of the human vocal tract. Existing methods for estimating formants from speech signals are computationally complex and subject to errors for certain type of speech sounds. This thesis describes a method for estimating vowel formant frequencies from Discrete Cosine Transform Coefficients (DCTC's), a form of cepstral coefficients, using a feedforward neural network with back-propagation training. Experimental results are based on a large multispeaker data base. The results are obtained for both a linear transformation and a feedforward neural network with a nonlinear hidden layer. In general, the neural network transformation is superior to the linear …
Encoding Phonetic Knowledge For Use In Hidden Markov Models Of Speech Recognition, Danming Qian
Encoding Phonetic Knowledge For Use In Hidden Markov Models Of Speech Recognition, Danming Qian
Electrical & Computer Engineering Theses & Dissertations
Hidden Markov models (HMM's) have achieved considerable success for isolated-word speaker-independent automatic speech recognition. However, the performance of an HMM algorithm is limited by its inability to discriminate between similar sounding words. The problem arises because all differences between speech patterns are treated as equally important. Thus the algorithm is particularly susceptible to confusions caused by phonetically-irrelevant differences. This thesis presents two types of preprocessing schemes as candidates for improving HMM performance. The aim is to maximize the differences between phonologically-distinct speech sounds while minimizing the effect of variations in phonologically-equivalent speech sounds. The preprocessors presented are a discrete cosine …
Design Of Infrasound-Detection System Via Adaptive Lmstde Algorithm, Camille S. Khalaf
Design Of Infrasound-Detection System Via Adaptive Lmstde Algorithm, Camille S. Khalaf
Electrical & Computer Engineering Theses & Dissertations
A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TOE) method, is first reviewed. An adaptive TUt approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is …