Faculty

Institution

Unit

Venue

Keith Michael Chugg

Professor of Electrical and Computer Engineering

University of Southern California

Affiliations

School of Engineering

Ming Hsieh Department of Electrical and Computer Engineering

Keith Michael Chugg is currently serving as a Ming Electrical And Computer Engineering Professor of Electrical and Computer Engineering at University of Southern California.

Honors

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Experiences

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Education

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Keith Michael Chugg

University of Southern California

Professor of Electrical and Computer Engineering

You can click a keyword to filter the displayed items

computer science signal processing communications systems computer engineering wireless communications digital signal processing iterative decoding algebraic coding theory channel estimation electrical engineering communication machine learning telecommunication networks deep learning graph theory communication engineering fading channels channel characterization iterative detection soft computing channel model communication theory networked system design ultra-wideband communication sparse neural network communication algorithm information theory communication security adaptive iterative detection computer vision information fusion machine vision channel modeling relay network adaptive algorithms channel capacity estimation graphical models low latency barrage relay networks distributed systems space-time processing channel equalization graph algorithms iterative message space-time codes field programmable gate array code representation radio communication linear block codes fast acquisition iterative algorithm unknown isi channels cpm signals electronics multimedia information processing multi-terminal information theory optical engineering parallel processing adaptive communication multi-carrier communication page-oriented optical memories frequency-selective fading channels soft information tanner graphs bandwidth efficiency control optimization information technology scientific computing radio frequency identification emerging memory technologies embedded machine learning pseudorandom number generator parametric uncertainty numerical simulations image communication vector space model systems engineering statistical signal processing signal design industrial informatics signal detection hardware algorithm

Notable Scholarly Works

Notable Federal Grants

Collaborators

Analysis and Calibration for Wideband Times-2 Interleaved Current-Steering Dacs. IEEE Transactions on Circuits and Systems I Regular Papers (2022)

Daniel BeauchampKeith M. Chugg

communications systemssystems engineeringengineeringelectronic circuitselectrical engineeringelectronicscircuit simulation

Approximation Capabilities of Neural Networks Using Morphological Perceptrons and Generalizations. 2014 48th Asilomar Conference on Signals, Systems and Computers (2022)

William ChangHassan HamadKeith M. Chugg

systems engineeringsignal processingneural networksapproximation capabilitiesmorphological perceptrons

Improved Analysis of Current-Steering Dacs Using Equivalent Timing Errors. 2022 IEEE International Symposium on Circuits and Systems (ISCAS) (2022)

Daniel BeauchampKeith M. Chugg

systems engineeringcircuit complexityengineeringcircuit designelectronic circuitsequivalent timing errorselectrical engineeringvlsi circuitcurrent-steering dacselectronicsmicroelectronicstiming analysiscircuit simulation

Analysis of the Average Sampling Frequency for Level Crossing Analog-To-Digital Converters. MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) (2021)

Mengkun JiKeith M. Chugg

communications systemsengineeringanalog-to-digital converterselectrical engineeringaverage sampling frequency

Deep-N-Cheap: An Automated Efficient and Extensible Search Framework for Cost-Effective Deep Learning. SN Computer Science (2021)

Sourya DeySara BabakniyaSaikrishna C. KanalaMarco PaolieriLeana GolubchikPeter A. BeerelKeith M. Chugg

artificial intelligencecomputer sciencedeep learningextensible search frameworkcost-effective deep learninginformation technologymachine learning

Linearization for High-Speed Current-Steering Dacs Using Neural Networks. (2021)

Daniel BeauchampKeith M. Chugg

automatic controlneural networkselectrical engineeringneural network (machine learning)high-speed current-steering dacs

Deep-N-Cheap: An Automated Search Framework for Low Complexity Deep Learning. arXiv (Cornell University) (2020)

Sourya DeySaikrishna C. KanalaKeith M. ChuggPeter A. Beerel

computer scienceautomated search frameworkmachine learningdeep learning

Neural Network Training With Approximate Logarithmic Computations. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2020)

Arnab SanyalPeter A. BeerelKeith M. Chugg

computer scienceneural networkcomputational neuroscienceapproximate logarithmic computationsmachine learning

Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks. arXiv (Cornell University) (2020)

Souvik KunduMahdi NazemiMassoud PedramKeith M. ChuggPeter A. Beerel

computer scienceconvolutional neural networkscomputer visiondeep learningpre-defined sparsitymachine learning

Machine Learning Based Image Calibration for a Twofold Time-Interleaved High Speed Dac. arXiv (Cornell University) (2019)

Daniel BeauchampKeith M. Chugg

computer scienceimage calibrationmachine learningdeep learning

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Keith Michael Chugg

Professor of Electrical and Computer Engineering

University of Southern California

Affiliations

School of Engineering

Ming Hsieh Department of Electrical and Computer Engineering

Keith Michael Chugg is currently serving as a Ming Electrical And Computer Engineering Professor of Electrical and Computer Engineering at University of Southern California.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Keith Michael Chugg

University of Southern California

Professor of Electrical and Computer Engineering

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Analysis and Calibration for Wideband Times-2 Interleaved Current-Steering Dacs. IEEE Transactions on Circuits and Systems I Regular Papers (2022)

Daniel BeauchampKeith M. Chugg

communications systemssystems engineeringengineeringelectronic circuitselectrical engineeringelectronicscircuit simulation

Approximation Capabilities of Neural Networks Using Morphological Perceptrons and Generalizations. 2014 48th Asilomar Conference on Signals, Systems and Computers (2022)

William ChangHassan HamadKeith M. Chugg

systems engineeringsignal processingneural networksapproximation capabilitiesmorphological perceptrons

Improved Analysis of Current-Steering Dacs Using Equivalent Timing Errors. 2022 IEEE International Symposium on Circuits and Systems (ISCAS) (2022)

Daniel BeauchampKeith M. Chugg

Analysis of the Average Sampling Frequency for Level Crossing Analog-To-Digital Converters. MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM) (2021)

Mengkun JiKeith M. Chugg

communications systemsengineeringanalog-to-digital converterselectrical engineeringaverage sampling frequency

Deep-N-Cheap: An Automated Efficient and Extensible Search Framework for Cost-Effective Deep Learning. SN Computer Science (2021)

Sourya DeySara BabakniyaSaikrishna C. KanalaMarco PaolieriLeana GolubchikPeter A. BeerelKeith M. Chugg

artificial intelligencecomputer sciencedeep learningextensible search frameworkcost-effective deep learninginformation technologymachine learning

Linearization for High-Speed Current-Steering Dacs Using Neural Networks. (2021)

Daniel BeauchampKeith M. Chugg

automatic controlneural networkselectrical engineeringneural network (machine learning)high-speed current-steering dacs

Deep-N-Cheap: An Automated Search Framework for Low Complexity Deep Learning. arXiv (Cornell University) (2020)

Sourya DeySaikrishna C. KanalaKeith M. ChuggPeter A. Beerel

computer scienceautomated search frameworkmachine learningdeep learning

Neural Network Training With Approximate Logarithmic Computations. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2020)

Arnab SanyalPeter A. BeerelKeith M. Chugg

computer scienceneural networkcomputational neuroscienceapproximate logarithmic computationsmachine learning

Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks. arXiv (Cornell University) (2020)

Souvik KunduMahdi NazemiMassoud PedramKeith M. ChuggPeter A. Beerel

computer scienceconvolutional neural networkscomputer visiondeep learningpre-defined sparsitymachine learning

Machine Learning Based Image Calibration for a Twofold Time-Interleaved High Speed Dac. arXiv (Cornell University) (2019)

Daniel BeauchampKeith M. Chugg

computer scienceimage calibrationmachine learningdeep learning

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10 / page

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Robert A. Scholtz

Institution

University of Southern California

radar signal processing

computer engineering

Salman Avestimehr

Institution

University of Southern California

information technology

information security

Natasha Devroye

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University of Illinois Chicago

cognitive radio

communication

Sundeep Rangan

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communications system

5g system

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optical communication systems

signal processing

Upamanyu Madhow

Institution

University of California, Santa Cruz

signal processing

localization

Shu Lin

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computer engineering

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University of Texas at Arlington

electrical engineering

computer science

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information theory

Ali Akansu

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information technology

signal detection