What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
His primary areas of study are Algorithm, Artificial intelligence, Detection theory, Underwater acoustic communication and Orthogonal frequency-division multiplexing.
His work carried out in the field of Algorithm brings together such families of science as Theoretical computer science, Detector, Control theory, Speech recognition and Probabilistic logic.
His Artificial intelligence research incorporates themes from Computer vision and Pattern recognition.
His studies deal with areas such as Statistic and Robustness as well as Detection theory.
He has researched Underwater acoustic communication in several fields, including Subcarrier, Underwater acoustics, Low-density parity-check code and Wideband.
Peter Willett interconnects MIMO, Electronic engineering and Decoding methods in the investigation of issues within Orthogonal frequency-division multiplexing.
His most cited work include:
- Multicarrier Communication Over Underwater Acoustic Channels With Nonuniform Doppler Shifts (598 citations)
- Sparse channel estimation for multicarrier underwater acoustic communication: From subspace methods to compressed sensing (545 citations)
- Censoring sensors: a low-communication-rate scheme for distributed detection (367 citations)
What are the main themes of his work throughout his whole career to date?
Peter Willett mostly deals with Algorithm, Artificial intelligence, Tracking, Pattern recognition and Sensor fusion.
His Algorithm study combines topics in areas such as Detector, Detection theory, Radar, Radar tracker and Signal processing.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Computer vision.
His Tracking study integrates concerns from other disciplines, such as Clutter and Filter.
His Pattern recognition research includes themes of Data reduction and Quantization.
His work is dedicated to discovering how Sensor fusion, Wireless sensor network are connected with Real-time computing and Communication channel and other disciplines.
He most often published in these fields:
- Algorithm (36.92%)
- Artificial intelligence (31.47%)
- Tracking (16.08%)
What were the highlights of his more recent work (between 2016-2021)?
- Algorithm (36.92%)
- Tracking (16.08%)
- Artificial intelligence (31.47%)
In recent papers he was focusing on the following fields of study:
His main research concerns Algorithm, Tracking, Artificial intelligence, Cramér–Rao bound and Upper and lower bounds.
His studies in Algorithm integrate themes in fields like Covariance, Estimator, Likelihood-ratio test, Noise measurement and Monte Carlo method.
His Estimator research includes elements of Azimuth, Fisher information and Control theory.
His Tracking study also includes
- Probabilistic logic that intertwine with fields like Clutter,
- Cardinal point which connect with Point.
As a member of one scientific family, he mostly works in the field of Artificial intelligence, focusing on Machine learning and, on occasion, Hidden Markov model.
His Cramér–Rao bound study combines topics from a wide range of disciplines, such as Point target, Pixel, Point spread function, Matched filter and Estimation.
Between 2016 and 2021, his most popular works were:
- A Scalable Algorithm for Tracking an Unknown Number of Targets Using Multiple Sensors (86 citations)
- Generalized Rao Test for Decentralized Detection of an Uncooperative Target (85 citations)
- Feature article: security of SCADA systems against cyber–physical attacks (33 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Algorithm
His primary scientific interests are in Algorithm, Tracking, Noise measurement, Stochastic process and Radar tracker.
The Algorithm study combines topics in areas such as Mathematical optimization, Covariance, Likelihood-ratio test and Sensor fusion.
His research investigates the connection between Sensor fusion and topics such as Probability density function that intersect with problems in Estimator.
Tracking is a primary field of his research addressed under Artificial intelligence.
His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Computer vision.
His Radar tracker study also includes fields such as
- Extended Kalman filter that intertwine with fields like Range, Sonar and Nonlinear system,
- Kalman filter which intersects with area such as Filter, Delay spread, Communication channel, Multipath propagation and Compressed sensing.
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