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Mahesh K. Banavar
Clarkson University
83Publications
12H-index
473Citations
Publications 83
Newest
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 10
Last.Cihan Tepedelenlioglu (ASU: Arizona State University)H-Index: 26
view all 8 authors...
In this paper, we present a unique Android-DSP (AJDSP) application which was built from the ground up to provide mobile laboratory and computational experiences for educational use. AJDSP provides a mobile intuitive environment for developing and running signal processing simulations in a user-friendly. It is based on a block diagram system approach to support signal generation, analysis, and processing. AJDSP is designed for use by undergraduate and graduate students and DSP instructors. Its ex...
#1Xue ZhangH-Index: 6
Last.Gowtham MunirajuH-Index: 1
view all 5 authors...
In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are used for localization, due to existing hardware constraints, fading channels play a crucial role in localization accuracy. In a location estimation formulation, the Cramer-Rao lower bound for localization error is derived under different assumptions on fading coefficients. For the same level of localization accuracy, t...
Last.Mahesh K. Banavar (Clarkson University)H-Index: 12
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This work in progress paper describes software that enables online machine learning experiments in an undergraduate DSP course. This software operates in HTML5 and embeds several digital signal processing functions. The software can process natural signals such as speech and can extract various features, for machine learning applications. For example in the case of speech processing, LPC coefficients and formant frequencies can be computed. In this paper, we present speech processing, feature ex...
#1Seema Rivera (Clarkson University)
#2Mahesh K. Banavar (Clarkson University)H-Index: 12
Last.Dana M. Barry (Clarkson University)H-Index: 5
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The central focus of this work-in-progress is to investigate the following: (1) What do the lesson plans created by teachers reveal about their understanding of science and engineering practices? (2) Will including programming exercises in all lesson plans improve STEM skills in general, and coding skills in particular? And (3) Will integrating science and engineering practices in high school lesson plans improve student retention in STEM and STEM-related areas? To answer these questions, we dev...
#1Gowtham Muniraju (ASU: Arizona State University)H-Index: 1
#2Cihan Tepedelenlioglu (ASU: Arizona State University)H-Index: 26
Last.Mahesh K. Banavar (Clarkson University)H-Index: 12
view all 5 authors...
The analysis of a distributed consensus algorithm for estimating the maximum of the node initial state values in a network is considered in the presence of communication noise. Conventionally, the maximum is estimated by updating the node state value with the largest received measurements in every iteration at each node. However, due to additive channel noise, the estimate of the maximum at each node has a positive drift at each iteration and this results in nodes diverging from the true max val...
#1Abhinav Dixit (ASU: Arizona State University)
#2Uday Shankar Shanthamallu (ASU: Arizona State University)H-Index: 2
Last.Photini Spanias (ASU: Arizona State University)H-Index: 3
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#1Sameeksha Katoch (ASU: Arizona State University)H-Index: 1
#2Gowtham Muniraju (ASU: Arizona State University)H-Index: 1
Last.Devarajan SrinivasanH-Index: 2
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This paper describes three methods used in the development of a utility-scale solar cyber-physical system. The study describes remote fault detection using machine learning approaches, power output optimization using cloud movement prediction and consensus-based solar array parameter estimation. Dynamic cloud movement, shading and soiling, lead to fluctuations in power output and loss of efficiency. For optimization of output power, a cloud movement prediction algorithm is proposed. Integrated f...
#1Sai Zhang (ASU: Arizona State University)H-Index: 4
Last.Mahesh K. Banavar (Clarkson University)H-Index: 12
view all 4 authors...
Abstract The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) g...
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