Explanipedia

Offline Stochastic Optimization of Black-Box Objective Functions Open

Juncheng Dong, Zihao Wu, Hamid Jafarkhani, Ali Pezeshki, Vahid Tarokh · 2024

Many challenges in science and engineering, such as drug discovery and communication network design, involve optimizing complex and expensive black-box functions across vast search spaces. Thus, it is essential to leverage existing data to…

Steinmetz Neural Networks for Complex-Valued Data Open

Shyam Venkatasubramanian, Ali Pezeshki, Vahid Tarokh · 2024

We introduce a new approach to processing complex-valued data using DNNs consisting of parallel real-valued subnetworks with coupled outputs. Our proposed class of architectures, referred to as Steinmetz Neural Networks, incorporates multi…

A Performance Bound for the Greedy Algorithm in a Generalized Class of String Optimization Problems Open

Brandon Van Over, Bowen Li, Edwin K. P. Chong, Ali Pezeshki · 2024

We present a simple performance bound for the greedy scheme in string optimization problems that obtains strong results. Our approach vastly generalizes the group of previously established greedy curvature bounds by Conforti and Cornuéjols…

Statistical estimation theory detection limits for label-free imaging Open

Lang Wang, Maxine Varughese, Ali Pezeshki, Randy A. Bartels · 2024

We provide valuable insights for researchers seeking to leverage label-free techniques for non-invasive imaging applications for biomedical research and clinical practice.

Data‐driven target localization using adaptive radar processing and convolutional neural networks Open

Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy , et al. · 2024

Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper presents a data‐driven approach to improve accuracy in radar…

RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications Open

Shyam Venkatasubramanian, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy, Vahid Tarokh · 2024

We present a large-scale dataset called RASPNet for radar adaptive signal processing (RASP) applications to support the development of data-driven models within the adaptive radar community. RASPNet exceeds 16 TB in size and comprises 100 …

Statistical estimation theory detection limits for label-free imaging Open

Lang Wang, Maxine Xii, Ali Pezeshki, Randy A. Bartels · 2024

The emergence of label-free microscopy techniques has significantly improved our ability to precisely characterize biochemical targets, enabling non-invasive visualization of cellular organelles and tissue organization. Each label-free met…

On Bounds for Greedy Schemes in String Optimization based on Greedy Curvatures Open

Bowen Li, Brandon Van Over, Edwin K. P. Chong, Ali Pezeshki · 2024

We consider the celebrated bound introduced by Conforti and Cornuéjols (1984) for greedy schemes in submodular optimization. The bound assumes a submodular function defined on a collection of sets forming a matroid and is based on greedy c…

Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound Open

Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy , et al. · 2024

In modern radar systems, precise target localization using azimuth and velocity estimation is paramount. Traditional unbiased estimation methods have utilized gradient descent algorithms to reach the theoretical limits of the Cramer Rao Bo…

Recursive Least Squares With Minimax Concave Penalty Regularization for Adaptive System Identification Open

Bowen Li, Suya Wu, Erin E. Tripp, Ali Pezeshki, Vahid Tarokh · 2024

We develop a recursive least squares (RLS) type algorithm with a minimax concave penalty (MCP) for adaptive identification of a sparse tap-weight vector that represents a communication channel. The proposed algorithm recursively yields its…

An Improved Greedy Curvature Bound in Finite-Horizon String Optimization with Application to a Sensor Coverage Problem Open

Brandon Van Over, Bowen Li, Edwin K. P. Chong, Ali Pezeshki · 2023

We study the optimization problem of choosing strings of finite length to maximize string submodular functions on string matroids, which is a broader class of problems than maximizing set submodular functions on set matroids. We provide a …

Super-resolution computational saturated absorption microscopy Open

Gabe Murray, Patrick A. Stockton, Jeffrey J. Field, Ali Pezeshki, Jeff Squier , et al. · 2023

Imaging beyond the diffraction limit barrier has attracted wide attention due to the ability to resolve previously hidden image features. Of the various super-resolution microscopy techniques available, a particularly simple method called …

Super resolution computational saturated absorption microscopy Open

Gabe Murray, Jeffrey J. Field, Patrick A. Stockton, Ali Pezeshki, Jeff Squier , et al. · 2023

Imaging beyond the diffraction limit barrier has attracted wide attention due to the ability to resolve image features that were previously hidden. Of the various super-resolution microscopy techniques available, a particularly simple meth…

Subspace Perturbation Analysis for Data-Driven Radar Target Localization Open

Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy , et al. · 2023

Recent works exploring data-driven approaches to classical problems in adaptive radar have demonstrated promising results pertaining to the task of radar target localization. Via the use of space-time adaptive processing (STAP) techniques …

The Effect of Foliar Application of Urea and Salicylic Acid on the Antibacterial Properties of Physalis alkekengi L. In vitro condition Open

Ali Pezeshki, Hassan Nourafcan, Mehdi Oraei, Naser Mohebalipour, Assad Assadi · 2022

Background and Aim: The Physalis alkekengi is a medicinal plant that has long been used in pharmaceutical, food and health products. Increasing and indiscriminate use of synthetic antibiotics against bacterial infections has increased drug…

Minimax Concave Penalty Regularized Adaptive System Identification Open

Bowen Li, Suya Wu, Erin E. Tripp, Ali Pezeshki, Vahid Tarokh · 2022

We develop a recursive least square (RLS) type algorithm with a minimax concave penalty (MCP) for adaptive identification of a sparse tap-weight vector that represents a communication channel. The proposed algorithm recursively yields its …

Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks Open

Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy , et al. · 2022

Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper presents a data-driven approach to improve accuracy in radar…

Group-Theoretic Wideband Radar Waveform Design Open

Kumar Vijay Mishra, Samuel Pinilla, Ali Pezeshki, A.R. Calderbank · 2022

We investigate the theory of affine groups in the context of designing radar waveforms that obey the desired wideband ambiguity function (WAF). The WAF is obtained by correlating the signal with its time-dilated, Doppler-shifted, and delay…

Toward Data-Driven STAP Radar Open

Shyam Venkatasubramanian, Chayut Wongkamthong, Mohammadreza Soltani, Bosung Kang, Sandeep Gogineni , et al. · 2022

Using an amalgamation of techniques from classical radar, computer vision,\nand deep learning, we characterize our ongoing data-driven approach to\nspace-time adaptive processing (STAP) radar. We generate a rich example dataset\nof receive…

Toward Data-Driven STAP Radar Open

Shyam Venkatasubramanian, Chayut Wongkamthong, Mohammadreza Soltani, Bosung Kang, Sandeep Gogineni , et al. · 2022

Using an amalgamation of techniques from classical radar, computer vision, and deep learning, we characterize our ongoing data-driven approach to space-time adaptive processing (STAP) radar. We generate a rich example dataset of received r…

Single-pixel fluorescent diffraction tomography Open

Patrick A. Stockton, Jeffery J. Field, Jeff Squier, Ali Pezeshki, Randy A. Bartels · 2020

Optical diffraction tomography (ODT) is an indispensable tool for studying objects in three dimensions. Until now, ODT has been limited to coherent light because spatial phase information is required to solve the inverse scattering problem…

Active Learning Model as a Way to Prepare Students for Knowledge Integration Open

Sourajeet Roy, Branislav M. Notaroš, Ali Pezeshki, Tom Chen, Thomas J. Siller , et al. · 2020

This work in progress describes an active learning classroom model developed by the authors as a key element of electrical engineering education. The three pillars of electrical engineering coursework are electronics, signals and systems, …

Bayesian Learning of Occupancy Grids Open

Christopher Robbiano, Edwin K. P. Chong, M.R. Azimi-Sadjadi, Louis L. Scharf, Ali Pezeshki · 2020

Occupancy grids encode for hot spots on a map that is represented by a two dimensional grid of disjoint cells. The problem is to recursively update the probability that each cell in the grid is occupied, based on a sequence of sensor measu…

Submodular optimization problems and greedy strategies: A survey Open

Yajing Liu, Edwin K. P. Chong, Ali Pezeshki, Zhenliang Zhang · 2020

Coordinating Complementary Waveforms for Suppressing Range Sidelobes in a Doppler Band Open

Wenbing Dang, Ali Pezeshki, Howard Caygill, William Moran, A.R. Calderbank · 2020

We present a general method for constructing radar transmit pulse trains and receive filters for which the radar point-spread function in delay and Doppler (radar cross-ambiguity function) is essentially free of range sidelobes inside a Do…

Submodular Optimization Problems and Greedy Strategies: A Survey Open

Yajing Liu, Edwin K. P. Chong, Ali Pezeshki, Zhenliang Zhang · 2019

The greedy strategy is an approximation algorithm to solve optimization problems arising in decision making with multiple actions. How good is the greedy strategy compared to the optimal solution? In this survey, we mainly consider two cla…

Why Math Matters: Demonstrating the Relevance of Mathematics in ECE Education Open

Yajing Liu, Ali Pezeshki, Sourajeet Roy, Branislav M. Notaroš, Tom Chen , et al. · 2018

This paper describes a team's efforts to transform the educational experience for electrical and computer engineering (ECE) students by demonstrating the importance of mathematics and the power of mathematical thinking. Math is a mainstay …

Work In Progress: Knowledge Integration to Understand Why Open

Tom Chen, Branislav M. Notaroš, Ali Pezeshki, Sourajeet Roy, Anthony A. Maciejewski , et al. · 2018

This work in progress describes how a multifaceted faculty team in the Department of Electrical and Computer Engineering (ECE) is redefining teaching and learning in the junior year of the undergraduate degree program. Also known as the ri…

Improved Bounds for the Greedy Strategy in Optimization Problems with Curvatures Open

Yajing Liu, Edwin K. P. Chong, Ali Pezeshki · 2017

Consider the problem of choosing a set of actions to optimize an objective function that is a real-valued polymatroid function subject to matroid constraints. The greedy strategy provides an approximate solution to the optimization problem…

Improved Bounds for the Greedy Strategy in Optimization Problems with Curvature Open

Yajing Liu, Edwin K. P. Chong, Ali Pezeshki · 2017

Consider the problem of choosing a set of actions to optimize an objective function that is a real-valued polymatroid function subject to matroid constraints. The greedy strategy provides an approximate solution to the optimization problem…

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