Search Results for author: Moeness G. Amin

Found 8 papers, 0 papers with code

Sparse Array Capon Beamformer Design Availing Deep Learning

no code implementations20 Aug 2021 Syed A. Hamza, Moeness G. Amin

The paper considers sparse array design for receive beamforming achieving maximum signal-to-interference plus noise ratio (MaxSINR).

Multi-Label Classification

Cognitive-Driven Optimization of Sparse Array Transceiver for MIMO Radar Beamforming

no code implementations4 Mar 2021 Weitong Zhai, Xiangrong Wang, Syed A. Hamza, Moeness G. Amin

Cognitive multiple-input multiple-output (MIMO) radar is capable of adjusting system parameters adaptively by sensing and learning in complex dynamic environment.

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

no code implementations20 Feb 2021 Syed A. Hamza, Weitong Zhai, Xiangrong Wang, Moeness G. Amin

The proposed approach entails an entwined design, i. e., jointly selecting the optimum transmit and receive sensor locations for accomplishing MaxSINR receive beamforming.

Efficient Near-Field Imaging Using Cylindrical MIMO Arrays

no code implementations22 Jan 2021 Shiyong Li, Shuoguang Wang, Moeness G. Amin, Guoqiang Zhao

Multiple-input multiple-output (MIMO) array based millimeter-wave (MMW) imaging has a tangible prospect in applications of concealed weapons detection.

RF Sensing for Continuous Monitoring of Human Activities for Home Consumer Applications

no code implementations21 Mar 2020 Moeness G. Amin, Arun Ravisankar, Ronny G. Guendel

Radar for indoor monitoring is an emerging area of research and development, covering and supporting different health and wellbeing applications of smart homes, assisted living, and medical diagnosis.

Medical Diagnosis Translation

Motion Classification using Kinematically Sifted ACGAN-Synthesized Radar Micro-Doppler Signatures

no code implementations19 Jan 2020 Baris Erol, Sevgi Zubeyde Gurbuz, Moeness G. Amin

The synthetic dataset is used to train a 19-layer deep convolutional neural network (DCNN) to classify micro-Doppler signatures acquired from an environment different from that of the dataset supplied to the adversarial network.

Activity Recognition General Classification

Radar Human Motion Recognition Using Motion States and Two-Way Classifications

no code implementations8 Nov 2019 Moeness G. Amin, Ronny G. Guendel

We perform classification of activities of daily living (ADL) using a Frequency-Modulated Continuous Waveform (FMCW) radar.

General Classification Translation

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