What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
Robert J. Marks mainly investigates Artificial intelligence, Artificial neural network, Algorithm, Machine learning and Perceptron.
His Artificial intelligence study combines topics in areas such as Computer vision, Electric power system and Pattern recognition.
His work deals with themes such as Stability, Data mining and Operating point, which intersect with Electric power system.
His Artificial neural network study incorporates themes from Training set and Remote sensing, Radiometry.
His Algorithm research includes themes of Image processing, Interpolation, Mathematical optimization, Signal processing and Iterative reconstruction.
His Perceptron study integrates concerns from other disciplines, such as Adaptive algorithm, Nonlinear programming, Adaptive system and Scaling.
His most cited work include:
- Electric load forecasting using an artificial neural network (1113 citations)
- Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (466 citations)
- The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals (389 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Artificial neural network, Electronic engineering, Algorithm and Optics.
His research integrates issues of Machine learning, Computer vision and Pattern recognition in his study of Artificial intelligence.
His Artificial neural network research is multidisciplinary, incorporating elements of Classifier, Thresholding and Electric power system.
His Electronic engineering research incorporates themes from Waveform, Radar, Amplifier, Input impedance and Electrical engineering.
Robert J. Marks interconnects Mathematical optimization, Extrapolation and Signal processing in the investigation of issues within Algorithm.
The various areas that he examines in his Optics study include Image processing and Fourier transform.
He most often published in these fields:
- Artificial intelligence (28.18%)
- Artificial neural network (21.82%)
- Electronic engineering (20.61%)
What were the highlights of his more recent work (between 2012-2021)?
- Electronic engineering (20.61%)
- Amplifier (10.00%)
- Radar (9.09%)
In recent papers he was focusing on the following fields of study:
Electronic engineering, Amplifier, Radar, Artificial intelligence and Input impedance are his primary areas of study.
His study on Electronic engineering also encompasses disciplines like
- Waveform which connect with Bandwidth,
- Transmitter which connect with Voltage,
- Ambiguity function together with Radar engineering details, Continuous-wave radar, Pulse-Doppler radar and Algorithm.
The Amplifier study combines topics in areas such as Control reconfiguration, Electrical impedance, Smith chart, Impedance matching and Tuner.
The Radar study which covers Transmission that intersects with Interference.
His Artificial intelligence research incorporates elements of Machine learning and Bounded function.
As part of one scientific family, he deals mainly with the area of Artificial neural network, narrowing it down to issues related to the Anomaly detection, and often Classifier.
Between 2012 and 2021, his most popular works were:
- Solving the Spectrum Crisis: Intelligent, Reconfigurable Microwave Transmitter Amplifiers for Cognitive Radar (65 citations)
- Direct algorithm for the Pareto load-pull optimisation of power-added efficiency and adjacent-channel power ratio (13 citations)
- A Peak-Search Algorithm for Load–Pull Optimization of Power-Added Efficiency and Adjacent-Channel Power Ratio (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
Robert J. Marks spends much of his time researching Electronic engineering, Input impedance, Amplifier, Radar engineering details and Radar.
His studies deal with areas such as Adjacent channel power ratio, Waveform, Electrical efficiency, Electrical engineering and Power bandwidth as well as Electronic engineering.
He works mostly in the field of Amplifier, limiting it down to topics relating to Smith chart and, in certain cases, Voltage source, Impedance bridging, Biasing and Control theory, as a part of the same area of interest.
His study looks at the relationship between Radar engineering details and fields such as Continuous-wave radar, as well as how they intersect with chemical problems.
His biological study spans a wide range of topics, including Transmitter and Radio spectrum.
His work on Bistatic radar is being expanded to include thematically relevant topics such as Algorithm.
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