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Exploiting Cross Domain Relationships For Target Recognition, Wei Wang 2015 University of Tennessee - Knoxville

Exploiting Cross Domain Relationships For Target Recognition, Wei Wang

Doctoral Dissertations

Cross domain recognition extracts knowledge from one domain to recognize samples from another domain of interest. The key to solving problems under this umbrella is to find out the latent connections between different domains. In this dissertation, three different cross domain recognition problems are studied by exploiting the relationships between different domains explicitly according to the specific real problems.

First, the problem of cross view action recognition is studied. The same action might seem quite different when observed from different viewpoints. Thus, how to use the training samples from a given camera view and perform recognition in another new view ...


Real-Time Digital Effects Processing Using Ios, Jonah W. Clinard 2015 California Polytechnic State University - San Luis Obispo

Real-Time Digital Effects Processing Using Ios, Jonah W. Clinard

Computer Engineering

In today’s society, we are seeing incredible improvements in terms of creating smaller technological devices that behave more and more like the personal computers of yesterday. Mobile “Smart” devices, in particular, are becoming incredibly powerful not just in terms of processing power, but in the fact that they are able to provide assistance to users in their everyday lives. Application developers are now able utilize the power and size of these devices, to create and realize ideas that would have been previously viewed as impossible. This project applies the fields of digital signal processing, music, and mobile application development ...


Hvdc Systems Fault Analysis Using Various Signal Processing Techniques, Benish Paily 2015 Dublin Institute of Technology

Hvdc Systems Fault Analysis Using Various Signal Processing Techniques, Benish Paily

Doctoral

The detection and fast clearance of faults are important for the safe and optimal operation of HVDC systems. In HVDC systems, various types of AC faults (rectifier & inverter side) and DC faults can occur. It is therefore necessary to detect the faults and classify them for better protection and diagnostics purposes. Various techniques for fault detection and classification in HVDC systems using signal processing techniques are presented and investigated in this research work. In this research work, it is shown that the wavelet transformation can effectively detect abrupt changes in system signals which are indicative of a fault. This research ...


Scaled Synthetic Aperture Radar System Development, Ryan K. Green 2015 Cal Poly SLO

Scaled Synthetic Aperture Radar System Development, Ryan K. Green

Master's Theses and Project Reports

Synthetic Aperture Radar (SAR) systems generate two dimensional images of a target area using RF energy as opposed to light waves used by cameras. When cloud cover or other optical obstructions prevent camera imaging over a target area, SAR can be substituted to generate high resolution images. Linear frequency modulated signals are transmitted and received while a moving imaging platform traverses a target area to develop high resolution images through modern digital signal processing (DSP) techniques. The motivation for this joint thesis project is to design and construct a scaled SAR system to support Cal Poly radar projects. Objectives include ...


Wireless Device Authentication Techniques Using Physical-Layer Device Fingerprint, Peng Hao 2015 The University of Western Ontario

Wireless Device Authentication Techniques Using Physical-Layer Device Fingerprint, Peng Hao

Electronic Thesis and Dissertation Repository

Due to the open nature of the radio signal propagation medium, wireless communication is inherently more vulnerable to various attacks than wired communication. Consequently, communication security is always one of the critical concerns in wireless networks. Given that the sophisticated adversaries may cover up their malicious behaviors through impersonation of legitimate devices, reliable wireless authentication is becoming indispensable to prevent such impersonation-based attacks through verification of the claimed identities of wireless devices.

Conventional wireless authentication is achieved above the physical layer using upper-layer identities and key-based cryptography. As a result, user authenticity can even be validated for the malicious attackers ...


Next Generation Of Product Search And Discovery, Kaiman Zeng 2015 Florida International University

Next Generation Of Product Search And Discovery, Kaiman Zeng

FIU Electronic Theses and Dissertations

Online shopping has become an important part of people’s daily life with the rapid development of e-commerce. In some domains such as books, electronics, and CD/DVDs, online shopping has surpassed or even replaced the traditional shopping method. Compared with traditional retailing, e-commerce is information intensive. One of the key factors to succeed in e-business is how to facilitate the consumers’ approaches to discover a product. Conventionally a product search engine based on a keyword search or category browser is provided to help users find the product information they need. The general goal of a product search system is ...


Adaptive Single-Phase Reclosing In Transmission Lines, Farzad Zhalefar 2015 The University of Western Ontario

Adaptive Single-Phase Reclosing In Transmission Lines, Farzad Zhalefar

Electronic Thesis and Dissertation Repository

This research work is mainly concerned about dealing with temporary short circuit faults in power system transmission lines. In fact, there are two types of electrical faults in power systems, namely temporary and permanent. When a fault is permanent, the only way to clear it is to de-energize the transmission line by opening the associated circuit breakers. However, in many cases the fault is not solid and is caused by objects such as flying birds or broken branches of trees. For these cases, electrical arc plays a major role. For such fault cases, it is also possible to de-energize the ...


Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla 2015 University of Dayton

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Electrical and Computer Engineering Faculty Publications

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly.

Once all data has been trained ...


Filters And Matrix Factorization, Myung-Sin Song, Palle E. T. Jorgensen 2015 Southern Illinois University Edwardsville

Filters And Matrix Factorization, Myung-Sin Song, Palle E. T. Jorgensen

SIUE Faculty Research, Scholarship, and Creative Activity

We give a number of explicit matrix-algorithms for analysis/synthesis

in multi-phase filtering; i.e., the operation on discrete-time signals which

allow a separation into frequency-band components, one for each of the

ranges of bands, say N , starting with low-pass, and then corresponding

filtering in the other band-ranges. If there are N bands, the individual

filters will be combined into a single matrix action; so a representation of

the combined operation on all N bands by an N x N matrix, where the

corresponding matrix-entries are periodic functions; or their extensions to

functions of a complex variable. Hence our setting ...


Analysis And Compensation Of Power Amplifier Distortions In Wireless Communication Systems, Sharath Manjunath 2015 The University of Western Ontario

Analysis And Compensation Of Power Amplifier Distortions In Wireless Communication Systems, Sharath Manjunath

Electronic Thesis and Dissertation Repository

Wireless communication devices transmit message signals which should possess desirable power levels for quality transmission. Power amplifiers are devices in the wireless transmitters which increase the power of signals to the desired levels, but produce nonlinear distortions due to their saturation property, resulting in degradation of the quality of the transmitted signal. This thesis talks about the analysis and performance of communication systems in presence of power amplifier nonlinear distortions.

First, the thesis studies the effects of power amplifier nonlinear distortions on communication signals and proposes a simplified design for identification and compensation of the distortions at the receiver end ...


Synthetic Aperture Focusing Technique Using The Envelope Function For Ultrasonic Imaging, W. Masri, Mani Mina, S. S. Udpa, L. Udpa, W. Lord 2015 Iowa State University

Synthetic Aperture Focusing Technique Using The Envelope Function For Ultrasonic Imaging, W. Masri, Mani Mina, S. S. Udpa, L. Udpa, W. Lord

Mani Mina

In traditional ultrasonic imaging systems, a transducer is scanned across the surface of a specimen at constant intervals. Synthetic aperture focusing techniques (SAFT) have been utilized extensively to process the RF data in order to enhance the signal-to-noise ratio of the image [1]. However, the implementation of the algorithm using sampled RF data has the disadvantage of requiring large memory and high-speed devices. These requirements can be reduced by using the envelope of the RF signal which involves processing the baseband signal. The envelope detection can be easily implemented as part of the receiver circuit.


Analysis Of Scanning Acoustic Microscopy Images Of Ic Chips, J. A. Khan, Mani Mina, L. Udpa, S. S. Udpa 2015 Iowa State University

Analysis Of Scanning Acoustic Microscopy Images Of Ic Chips, J. A. Khan, Mani Mina, L. Udpa, S. S. Udpa

Mani Mina

The detection, isolation, and characterization of flaws in components represent a critical need in manufacturing and quality control. Nondestructive testing (NDT) provides an effective way of inspecting materials for ensuring the quality and integrity of products and systems. Consequently, nondestructive inspection finds extensive application in several industries such as steel, nuclear and electronic industries for the evaluation of complex test objects with minimal interruption of routine operations[1].


Optimum Filter Based Techniques For Data Fusion, J. Yim, S. S. Udpa, Mani Mina, L. Udpa 2015 Iowa State University

Optimum Filter Based Techniques For Data Fusion, J. Yim, S. S. Udpa, Mani Mina, L. Udpa

Mani Mina

The growing complexity of inspection needs in the industrial workplace has contributed to an increasing interest in data fusion techniques. The interest in such methods have been fueled by a perception that classical approaches, involving the use of a single inspection methodology, are sometimes inadequate for capturing all the information necessary for characterizing the test specimen. It is often possible to employ two or more inspection techniques or measurement conditions for evaluating the specimen. Each test may provide a limited but slightly different perspective of the state the test object. Operators have traditionally combined the information from the test results ...


An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk 2015 Portland State University

An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk

Lisa M. Zurk

In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.


Semi-Blind Simo Flat-Fading Channel Estimation In Unknown Spatially Correlated Noise Using The Em Algorithm, Zhengdao Wang, Wei Mo, Aleksandar Dogandžić 2015 Iowa State University

Semi-Blind Simo Flat-Fading Channel Estimation In Unknown Spatially Correlated Noise Using The Em Algorithm, Zhengdao Wang, Wei Mo, Aleksandar Dogandžić

Zhengdao Wang

We present a maximum likelihood (ML) method for semi-blind estimation of single-input multi-output (SIMO) flat-fading channels in spatially correlated noise having unknown covariance. An expectation-maximization (EM) algorithm is utilized to compute the ML estimates of the channel and spatial noise covariance. We derive the Crame´r-Rao bound (CRB) matrix for the unknown parameters and present a symbol detector that utilizes the EM channel estimates. Numerical simulations demonstrate the performance of the proposed method.


Exploring Hidden Coherent Feature Groups And Temporal Semantics For Multimedia Big Data Analysis, Yimin Yang 2015 School of Computing and Information Sciences

Exploring Hidden Coherent Feature Groups And Temporal Semantics For Multimedia Big Data Analysis, Yimin Yang

FIU Electronic Theses and Dissertations

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with ...


Location Estimation In Wireless Communication Systems, Kejun Tong 2015 The University of Western Ontario

Location Estimation In Wireless Communication Systems, Kejun Tong

Electronic Thesis and Dissertation Repository

Localization has become a key enabling technology in many emerging wireless applications and services. One of the most challenging problems in wireless localization technologies is that the performance is easily affected by the signal propagation environment. When the direct path between transmitter and receiver is obstructed, the signal measurement error for the localization process will increase significantly. Considering this problem, we first propose a novel algorithm which can automatically detect and remove the obstruction and improve the localization performance in complex environment. Besides the environmental dependency, the accuracy of target location estimation is highly sensitive to the positions of reference ...


Compressed Sensing In Resource-Constrained Environments: From Sensing Mechanism Design To Recovery Algorithms, Shuangjiang Li 2015 University of Tennessee - Knoxville

Compressed Sensing In Resource-Constrained Environments: From Sensing Mechanism Design To Recovery Algorithms, Shuangjiang Li

Doctoral Dissertations

Compressed Sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. It is promising that CS can be utilized in environments where the signal acquisition process is extremely difficult or costly, e.g., a resource-constrained environment like the smartphone platform, or a band-limited environment like visual sensor network (VSNs). There are several challenges to perform sensing due to the characteristic of these platforms, including, for example, needing active user involvement, computational and storage limitations and lower transmission capabilities. This dissertation focuses on the study ...


Speaker Dependent Voice Recognition Using Discrete Wavelet Transform, Angelo Beltran Jr., Ericson Dimaunahan, Donde Deveras 2015 SelectedWorks

Speaker Dependent Voice Recognition Using Discrete Wavelet Transform, Angelo Beltran Jr., Ericson Dimaunahan, Donde Deveras

Innovative Research Publications IRP India

This paper presents effective and robust method for the extracting of features in the speaker dependent voice recognition. Based on the time-frequency multi-resolution property of wavelet transform, the input speech signal is decomposed into various frequency channels. The major issues concerning the design in this paper for wavelet based speaker voice recognition system are choosing the optimal wavelets for the speech signals, decomposition level in the discrete wavelet transform, and selecting the feature vectors from the wavelet coefficients. And finally, the wavelet-based voice recognition system and its performance are discussed and highlighted.


Automatic Detection And Denoising Of Signals In Large Geophysical Datasets, Gabriel O. Trisca 2015 Boise State University

Automatic Detection And Denoising Of Signals In Large Geophysical Datasets, Gabriel O. Trisca

Boise State University Theses and Dissertations

To fully understand the complex interactions of various phenomena in the natural world, scientific disciplines such as geology and seismology increasingly rely upon analyzing large amounts of observations. However, data collection is growing at a faster rate than what is currently possible to analyze through traditional approaches. These datasets, supplied by the increasing use of sensors and remote sensing, require specialized computer programs to effectively analyze complex and expansive volumes of data.

Elaborating on existing geophysical data processing approaches for infrasound data collected from an avalanche-prone area, this project proposes new techniques for processing large geophysical datasets. These improved techniques ...


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