Efficient Importance sampling Simulations for Digital Communication Systems
Importance sampling is a- modified. Monte Carlo simulation technique which can dramatically reduce the computational cost of the Monte Carlo method. A complete development is presented for its use in...
View ArticleComputing Torque and Related Output Variables of a Switched ReluctanceMachine...
The normal procedure industry employs in designing a Switched Reluctance Machine (SRM) is to construct and test a prototype to determine the machine's actual output characteristics. This procedure is...
View ArticleExploiting Fine-Grain Concurrency Analytical Insights in Superscalar...
This dissertation develops analytical models to provide insight into various design issues associated with superscalar-type processors, i.e., the processors capable of executing multiple instructions...
View ArticleBlockwise Transform Image Coding Enhancement and Edge Detection
The goal of this thesis is high quality image coding, enhancement and edge detection. A unified approach using novel fast transforms is developed to achieve all three objectives. Requirements are low...
View ArticleToward a Robust Minimum Variance Beamformer for Multi-Rank Signal Via...
A variation of Minimum Variance Distortionless Response (MVDR) based Match Field Processing (MFP) referred to as Semi-coherent MVDR MFP has been developed; Initial simulation results presented here...
View ArticleMethodologies for Voltage Contingency Ranking
Contingency studies in interconnected electric power systems are performed to assess the capability of a system to withstand disturbances caused by equipment outages and other factors, and are...
View ArticleData Structures and Sparsity in a Digital Simulation of an HVDC Link
An earlier algorithm for the detailed simulation of the High Voltage Direct Current (HVDC) link using the tensor approach was modified to improve the runtime speed. The runtime, approximately eleven...
View ArticleNeural Networks for Constrained Optimization Problems
This paper is concerned with utilizing neural networks and analog circuits to solve constrained optimization problems. A novel neural network architecture is proposed for solving a class of nonlinear...
View ArticleGeneralized 'Probe' Model for Arbitrary Dephasing Mechanisms
It has been shown earlier that in the linear response regime, dephasing by point scatterers (within the self-consistent Born approximation) can be visualized in terms of point voltage probes attached...
View ArticleMinimizing Quotient Space Norms Using Penalty Functions
A penalty function method approach is proposed to solve the general problem of quotient space norms minimization. A new class of penalty functions is introduced which allows one to transform...
View ArticleWide and Deep Neural Networks in Remote Sensing: A Review
Wide and deep neural networks in multispectral and hyperspectral image classification are discussed. Wide versus deep networks have always been a topic of intense interest. Deep networks mean large...
View ArticleDISC: A Method for Dynamic Intelligent Scheduling and Control of...
This work studies the use of intelligence-guided control of reconfigurable parallel processing systems. A reconfigurable architecture is one that can be partitioned into several independent virtual...
View ArticleLadder Networks for Semi-Supervised Hyperspectral Image Classification
We discuss the ladder network to perform hyperspectral image classification in a semi-supervised setting. The ladder network distinguishes itself from other semi-supervised methods by jointly...
View ArticleComposable, Sound Transformations of Nested Recursion and Loops
Scheduling transformations reorder a program’s operations to improve locality and/or parallelism. The polyhedral model is a general framework for composing and applying instancewise scheduling...
View ArticleParallel Multistage Wide Neural Network
Deep learning networks have achieved great success in many areas such as in large scale image processing. They usually need large computing resources and time, and process easy and hard samples...
View ArticleUnifying AoI Minimization and Remote Estimation — Optimal Sensor/Controller...
The ubiquitous usage of communication networks in modern sensing and control applications has kindled new interests on the timing coordination between sensors and controllers, i.e., how to use the...
View ArticleDistribution-oblivious Online Algorithms for Age-of-Information Penalty...
The ever-increasing needs of supporting real-time applications have spurred new studies on minimizing Age-of-Information (AoI), a novel metric characterizing the data freshness of the system. This...
View ArticleOutdated Measurements Are Still Useful For Multi-Sensor Linear Control...
Linear systems are a widely used model for the control tasks of modern cyber physical systems around their stationary state(s), e.g., smart grids, remote health applications, and autonomous driving...
View ArticleSynthetic Aperture Radar Imaging
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...
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