Engineering Commons^™

Sparse Ensemble Networks For Hypserspectral Image Classification, Rakesh Kumar Iyer, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

We explore the efficacy of sparsity and ensemble model in the classification of hyperspectral images, a pivotal task in remote sensing applications. While Convolutional Neural Networks (CNNs) and Transformer models have shown promise in this domain, each exhibits distinct limitations; CNNs excel in capturing the spatial/local features but falter to capture spectral features, whereas Transformers captures the spectral features at the expense of spatial features. Furthermore, the computational cost associated with training several independent CNN and Transformer networks becomes expensive. To address these limitations, we propose a novel ensemble framework comprising pruned CNNs and Transformers, optimizing both spatial and spectral …

Synthetic Aperture Radar Imaging, Srivatsan Ravichandran, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Simulation programs are used to locate the positions of the input target points and generate a 2D SAR image with the Range Migration Algorithm. Using the same methodology, we can create a scene geometry using the concept of Point cloud and run the simulation program to generate raw SAR data.

Natural Language Processing For Novel Writing, Leqing Qu, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

No abstract provided.

Multi-Resolution Codebook And Adaptive Beamforming Sequence Design For Millimeter Wave Beam Alignment, Song Noh, Michael D. Zoltowski, David J. Love

Department of Electrical and Computer Engineering Technical Reports

Millimeter wave (mmWave) communication is expected to be widely deployed in fifth generation (5G) wireless networks due to the substantial bandwidth available at mmWave frequencies. To overcome the higher path loss observed at mmWave bands, most prior work focused on the design of directional beamforming using analog and/or hybrid beamforming techniques in largescale multiple-input multiple-output (MIMO) systems. Obtaining potential gains from highly directional beamforming in practical systems hinges on sufficient levels of channel estimation accuracy, where the problem of channel estimation becomes more challenging due to the substantial training overhead needed to sound all directions using a high-resolution narrow beam. …

General Transformations For Gpu Execution Of Tree Traversals, Michael Goldfarb, Youngjoon Jo, Milind Kulkarni

Department of Electrical and Computer Engineering Technical Reports

With the advent of programmer-friendly GPU computing environments, there has been much interest in offloading workloads that can exploit the high degree of parallelism available on modern GPUs. Exploiting this parallelism and optimizing for the GPU memory hierarchy is well-understood for regular applications that operate on dense data structures such as arrays and matrices. However, there has been significantly less work in the area of irregular algorithms and even less so when pointer-based dynamic data structures are involved. Recently, irregular algorithms such as Barnes-Hut and kd-tree traversals have been implemented on GPUs, yielding significant performance gains over CPU implementations. However, …

Theory And Applications Of Compressive Sensing, Atul Divekar, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

This thesis develops algorithms and applications for compressive sensing, a topic in signal processing that allows reconstruction of a signal from a limited number of linear combinations of the signal. New algorithms are described for common remote sensing problems including superresolution and fusion of images. The algorithms show superior results in comparison with conventional methods. We describe a method that uses compressive sensing to reduce the size of image databases used for content based image retrieval. The thesis also describes an improved estimator that enhances the performance of Matching Pursuit type algorithms, several variants of which have been developed for …

Throughput And Delay Analysis On Uncoded And Coded Wireless Broadcast With Hard Deadline Constraints, Xiaohang Li, Chih-Chun Wang, Xiaojun Lin

Department of Electrical and Computer Engineering Technical Reports

Multimedia streaming applications have stringent QoS requirements. Typically each packet is associated with a packet delivery deadline. This work models and considers realtime streaming broadcast over the downlink of a single cell. The broadcast capacity of the system subject to deadline constraints are studied for both uncoded and coded wireless broadcast schemes. For the uncoded scenario, an optimal transmission policy is devised based on finite-horizon dynamic programming, and a closed-form expression of the optimal throughput is developed in the asymptotic regime, as the size of the file approaches infinity. For the coded scenario, the optimal capacity in the asymptotic regime …

Probabilistic Matching Pursuit For Compressive Sensing, Atul Divekar, Okan K. Ersoy

Department of Electrical and Computer Engineering Technical Reports

Compressive sensing investigates the recovery of a signal that can be sparsely represented in an orthonormal basis or overcomplete dictionary given a small number of linear combinations of the signal. We present a novel matching pursuit algorithm that uses the measurements to probabilistically select a subset of bases that is likely to contain the true bases constituting the signal. The algorithm is successful in recovering the original signal in cases where deterministic matching pursuit algorithms fail. We also show that exact recovery is possible when the number of nonzero coefficients is upto one less than the number of measurements. This …

H-Matrix-Based Fast Direct Finite Element Solver For Large-Scale Electromagnetic Analysis, Haixin Liu, Dan Jiao

Department of Electrical and Computer Engineering Technical Reports

In this work, we prove that the sparse matrix resulting from a finite-element-based analysis of electrodynamic problems can be represented by an H-matrix without any approximation, and the inverse of this sparse matrix has a data-sparse H-matrix approximation with error well controlled. Based on this proof, we develop an H-matrix-based direct finite-element solver of O(kNlogN) memory complexity and O(k2Nlog2N) time complexity for solving electromagnetic problems, where k is a small variable that is adaptively determined based on accuracy requirements, and N is the number of unknowns. Both inversebased and LU-based direct solutions are developed. The LU-based solution is further accelerated …

A Theoretically Rigorous Full-Wave Finite-Element-Based Solution Of Maxwell's Equations From Dc To High Frequencies, Jianfang Zhu, Dan Jiao

Department of Electrical and Computer Engineering Technical Reports

It has been observed that finite element based solutions of full-wave Maxwell's equations break down at low frequencies. In this paper, we present a theoretically rigorous method to fundamentally eliminate the low-frequency breakdown problem. The key idea of this method is that the original frequency-dependent deterministic problem can be rigorously solved from a generalized eigenvalue problem that is frequency independent. In addition, we found that the zero eigenvalues of the generalized eigenvalue problem cannot be obtained as zeros because of finite machine precision. We hence correct the inexact zero eigenvalues to be exact zeros. The validity and accuracy of the …

Camouflaging Timing Channels In Web Traffic, Sarah H. Sellke, Chih-Chun Wang, Saurabh Bagchi, Ness B. Shroff

Department of Electrical and Computer Engineering Technical Reports

Web traffic accounts for more than half of Internet traffic today. Camouflaging covert timing channels in Web traffic would be advantageous for concealment. In this paper, we investigate the possibility of disguising network covert timing channels as HTTP traffic to avoid detection. Extensive research has shown that Internet traffic, including HTTP traffic, exhibits self-similarity and long range persistence. Existing covert timing channels that mimic i.i.d. legitimate traffic cannot imitate HTTP traffic because these covert traffic patterns are not long range dependent. The goal of this work is to design a covert timing channel that can be camouflaged as HTTP traffic. …

A Parallel Direct Solver For The Simulation Of Large-Scale Power/Ground Networks, Stephen Cauley, Venkataramanan Balakrishnan, Cheng-Kok Koh

Department of Electrical and Computer Engineering Technical Reports

We present an algorithm for the fast and accurate simulation of power/ground mesh structures. Our method is a direct (non-iterative) approach for simulation based upon a parallel matrix inversion algorithm. Through the use of additional computational resources, this distributed computing technique facilitates the simulation of large-scale power/ground networks. In addition, the new dimension of flexibility provided by our algorithm allows for a more accurate analysis of power/ground mesh structures using RLC interconnect models. Specifically, we offer a method that employs a sparse approximate inverse technique to consider more reluctance coupling terms for increased accuracy of simulation. The inclusion of additional …

Ccack: Efficient Network Coding Based Opportunistic Routing Through Cumulative Coded Acknowledgments, Dimitrios Koutsonikolas, Chih-Chun Wang, Y. Charlie Hu

Department of Electrical and Computer Engineering Technical Reports

The use of random linear network coding (NC) has significantly simplified the design of opportunistic routing (OR) protocols by removing the need of coordination among forwarding nodes for avoiding duplicate transmissions. However, NC-based OR protocols face a new challenge: How many coded packets should each forwarder transmit? To avoid the overhead of feedback exchange, most practical existing NC-based OR protocols compute offline the expected number of transmissions for each forwarder using heuristics based on periodic measurements of the average link loss rates and the ETX metric. Although attractive due to their minimal coordination overhead, these approaches may suffer significant performance …

Defining And Implementing Commutativity Conditions For Parallel Execution, Milind Kulkarni, Dimitrios Prountzos, Donald Nguyen, Keshav Pingali

Department of Electrical and Computer Engineering Technical Reports

Irregular applications, which manipulate complex, pointer-based data structures, are a promising target for parallelization. Recent studies have shown that these programs exhibit a kind of parallelism called amorphous data-parallelism. Prior approaches to parallelizing these applications, such as thread-level speculation and transactional memory, often obscure parallelism because they do not distinguish between the concrete representation of a data structure and its semantic state; they conflate metadata and data.

Exploiting the semantic commutativity of methods in complex data structures is a promising approach to exposing more parallelism. Prior work has shown that abstract locks can be used to capture a subset of …

Multicore-Aware Reuse Distance Analysis, Derek L. Schuff, Benjamin S. Parsons, Vijay S. Pai

Department of Electrical and Computer Engineering Technical Reports

This paper presents and validates methods to extend reuse distance analysis of application locality characteristics to shared-memory multicore platforms by accounting for invalidation-based cache-coherence and inter-core cache sharing. Existing reuse distance analysis methods track the number of distinct addresses referenced between reuses of the same address by a given thread, but do not model the effects of data references by other threads. This paper shows several methods to keep reuse stacks consistent so that they account for invalidations and cache sharing, either as references arise in a simulated execution or at synchronization points. These methods are evaluated against a Simics-based …

An Error Bound For The Sensor Scheduling Problem, Wei Zhang, Jianghai Hu, Michael P. Vitus

Department of Electrical and Computer Engineering Technical Reports

The sensor scheduling problem tries to select one out of multiple available sensors at each time step to minimize a weighted sum of all the estimation errors over a certain time horizon. The problem can be solved by enumerating all the possible schedules. The complexity of such an enumeration approach grows exponentially fast as the horizon increases. In this report, by introducing some numerical relaxation parameter, we develop an efficient way to compute a suboptimal sensor schedule. It is shown that by choosing the relaxation parameter small enough, the performance of the obtained suboptimal schedule can be made arbitrarily close …

Evaluation Of Regression Ensembles On Drug Design Datasets, M. Fatih Amasyali, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Studies on drug design datasets are continuing to grow. These datasets are usually known as hard modeled, having a large number of features and a small number of samples. The most common problems in the drug design area are of regression type. Committee machines (ensembles) have become popular in machine learning because of their high performance. In this study, dynamics of ensembles on regression related drug design problems are investigated on a big dataset collection. The study tries to determine the most successful ensemble algorithm, the base algorithm-ensemble pair having the best / worst results, the best successful single algorithm, …

Prediction Of Disorder With New Computational Tool: Bvdea, Irem Ersoz Kaya, Turgay Ibrikci, Okan K. Ersoy

Department of Electrical and Computer Engineering Technical Reports

Motivation: Recognizing that many intrinsically disordered regions in proteins play key roles in vital functions and also in some diseases, identification of the disordered regions has became a demanding process for structure prediction and functional characterization of proteins. Therefore, many studies have been motivated on accurate prediction of disorder. Mostly, machine learning techniques have been used for dealing with the prediction problem of disorder due to the capability of extracting the complex relationships and correlations hidden in large data sets. Results: In this study, a novel method, named Border Vector Detection and Extended Adaptation (BVDEA) was developed for predicting disorder …

A Study Of Meta Learning For Regression, M. Fatih Amasyali, Okan K. Ersoy

Department of Electrical and Computer Engineering Technical Reports

In regression applications, there is no single algorithm which performs well with all data since the performance of an algorithm depends on the dataset used. In practice, different algorithms / approaches are tried, and the best one is selected in each application. It is meaningful to ask whether there is a different way instead of running such tedious experiments. In meta learning studies, one investigates clues for the performance of an algorithm over a dataset using several features of the dataset. In this context, it is important to estimate which dataset features (meta features) are most significant for the performance …

How To Keep Your Head Above Water While Detecting Errors, Saurabh Bagchi, Ignacio Laguna, Fahad Arshad, David M. Grothe

Department of Electrical and Computer Engineering Technical Reports

Abstract. Today’s distributed systems need runtime error detection to catch errors arising from software bugs, hardware errors, or unexpected operating conditions. A prominent class of error detection techniques operates in a stateful manner, i.e., it keeps track of the state of the application being monitored and then matches state-based rules. Large-scale distributed applications generate a high volume of messages that can overwhelm the capacity of a stateful detection system. An existing approach to handle this is to randomly sample the messages and process the subset. However, this approach, leads to non-determinism with respect to the detection system’s view of what …

A Study Of The Discrete-Time Switched Lqr Problem, Wei Zhang, Jianghai Hu, Alessandro Abate

Department of Electrical and Computer Engineering Technical Reports

This paper studies the discrete-time switched LQR (DSLQR) problem based on a dynamic programming approach. One contribution of this paper is the analytical characterization of both the value function and the optimal hybridcontrol strategy of the DSLQR problem. Their connections to the Riccati equation and the Kalman gain of the classical LQR problem are also discussed. Several interesting properties of the value functions are derived. In particular, we show that under some mild conditions, the family of finite-horizon value functions of the DSLQR problem is homogeneous (of degree 2), uniformly bounded over the unit ball, and converges exponentially fast to …

Support Vector Selection And Adaptation For Classification Of Remote Sensing Images, Gulsen Taskin Kaya, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Classification of nonlinearly separable data by nonlinear support vector machines is often a difficult task especially due to the necessity of a choosing a convenient kernel type. In this study, we propose a new classification method called support vector selection and adaptation (SVSA) that is applicable to both linearly and nonlinearly separable data in terms of some reference vectors generated by processing of support vectors obtained from the linear SVM. The method consists of two steps called selection and adaptation. In these two steps, once the support vectors are obtained by a linear SVM, some of them are rejected and …

Stabilizing Switched Linear Systems With Unstabilizable Subsystems, Wei Zhang, Jianghai Hu, Alessandro Abate

Department of Electrical and Computer Engineering Technical Reports

Abstract This paper studies the exponential stabilization problem for discrete-time switched linear systems based on a control-Lyapunov function approach. A number of versions of converse control-Lyapunov function theorems are proved and their connections to the switched LQR problem are derived. It is shown that the system is exponentially stabilizable if and only if there exists a finite integer N such that the N-horizon value function of the switched LQR problem is a control-Lyapunov function. An efficient algorithm is also proposed which is guaranteed to yield a control-Lyapunov function and a stabilizing strategy whenever the system is exponentially stabilizable.

Remote Sensing Methods By Compressive Sensing, Atul Divekar, Okan Ersoy

Department of Electrical and Computer Engineering Technical Reports

Compressive Sensing is a recently developed technique that exploits the sparsity of naturally occurring signals and images to solve inverse problems when the number of samples is less than the size of the original signal. We apply this technique to solve underdetermined inverse problems that commonly occur in remote sensing, including superresolution, image fusion and deconvolution. We use l1-minimization to develop algorithms that perform as well as or better than conventional methods for these problems. Our algorithms use a library of samples from similar images or a model for the image to be reconstructed to express the image as a …

An Empirical Study Of Performance Benefits Of Network Coding In Multihop Wireless Networks, Y. Charlie Hu, Chih-Chun Wang

Department of Electrical and Computer Engineering Technical Reports

Recently, network coding has gained much popularity and several practical routing schemes have been proposed for wireless mesh networks that exploit interflow network coding for improved throughput. However, the evaluation of these protocols either assumed simple topologies and traffic patterns such as opposite flows along a single chain, or small, dense networks which have ample overhearing of each other’s transmissions in addition to many overlapping flows. In this paper, we seek to answer the fundamental question: how much performance benefit from network coding can be expected for general traffic patterns in a moderate-sized wireless mesh network? We approach this question …

Nesting Forward-Mode Ad In A Functional Framework, Jeffrey M. Siskind, Barak A. Pearlmutter

Department of Electrical and Computer Engineering Technical Reports

We discuss the augmentation of a functional-programming language with a derivative- taking operator implemented with forward-mode automatic differentiation (AD). The primary technical difficulty in doing so lies in ensuring correctness in the face of nested invocation of that operator, due to the need to distinguish perturbations introduced by distinct invocations. We exhibit a series of implementations of a referentially- transparent forward-mode-AD derivative-taking operator, each of which uses a different non-referentially-transparent mechanism to distinguish perturbations. Even though the forward-mode-AD derivative-taking operator is itself referentially transparent, we hypothesize that one cannot correctly formulate this operator as a function definition in current pure …

Inferring Undesirable Behavior From P2p Traffic Analysis, Ruben Torres, Mohammad Hajjat, Sanjay G. Rao, Marco Mellia, Maurizio Munafo

Department of Electrical and Computer Engineering Technical Reports

ABSTRACT While peer-to-peer (P2P) systems have emerged in popularity in recent years, their large-scale and complexity make them difficult to reason about. In this paper, we argue that systematic analysis of traffic characteristics of P2P systems can reveal a wealth of information about their behavior, and highlight potential undesirable activities that such systems may exhibit. As a first step to this end, we present an offline and semi-automated approach to detecting undesirable behavior. Our analysis is applied on real traffic traces collected from a Point-of-Presence (PoP) of a national-wide ISP in which over 70% of the total traffic is due …

Distance Estimation Algorithm For Stereo Pair Images, Edwin Tjandranegara

Department of Electrical and Computer Engineering Technical Reports

Various algorithms have been proposed for estimating camera distance from objects in digital stereo pair videos and images. Existing algorithms assume that digital images were taken with pan and tilt cameras or assume that the angles between the cameras and the object are known. The algorithm that we are proposing has the ability to calculate distance from the camera plane to the object plane, where the cameras do not have the ability to pan and tilt nor the angles between the cameras and the object are known beforehand.

Development And Operation Of Buried Channel Charge Coupled Devices In 6h Silicon Carbide, Scott T. Sheppard, Michael R. Melloch, James A. Cooper Jr.

Department of Electrical and Computer Engineering Technical Reports

Silicon carbide is a wide bandgap semiconductor that is well suited for high power, high temperature electronic devices due to its remarkable electronic and thermal properties. Photosensitive devices in the 6H polytype of Sic have also been demonstrated, showing high sensitivity in ultraviolet wavelengths near 270 nm. Furthermore, the native oxide on Sic is silicon dioxide, meaning that SIC can be thermally oxidized to form a high quality gate dielectric, making metal-oxide-semiconductor (MOS) devices possible. These qualities make silicon carbide ideal for constructing UV sensitive CCD imagers. 'This work investigates the feasibility for developing imagers in Sic through the fabrication …

The Analysis, Simulation, And Implementation Of Control Strategies For A Pulsewidth Modulated Induction Motor Drive, Scott D. Roller, Chee Mun Ong

Department of Electrical and Computer Engineering Technical Reports

The purpose of this research is to analyze, simulate, and compare two different control strategies for a variable speed pulsewidth modulated induction motor drive, and implement one of the control strategies using the Motorola MC68F333 inicrocontroller. The two strategies examined in this technical report are volts per hertz control and field oriented control. The benefits and limitations of each strategy are examined through theoretical analysis. Verification of the analysis is performed by simulating thc strategies usmg the Simulink toolbox of Matlab. The Motorola microcontroller is then used to generate both edge-aligned and center-aligned pulsewidth modulated drive signals for a three …