What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Mathematical analysis
His primary areas of study are Control theory, Nonlinear system, Artificial neural network, Mathematical optimization and Stochastic process.
His studies in Control theory integrate themes in fields like Upper and lower bounds, Estimator and Applied mathematics.
His Nonlinear system study combines topics in areas such as Control engineering and Control system.
His work deals with themes such as Finite time, Memristor and Lyapunov function, which intersect with Artificial neural network.
His work carried out in the field of Mathematical optimization brings together such families of science as Differentiable function, Multi-agent system and Fuzzy logic.
His Stochastic process study combines topics from a wide range of disciplines, such as Filtering problem, Computer security model, Markov chain and Stochastic neural network.
His most cited work include:
- A survey of deep neural network architectures and their applications (1147 citations)
- Event-triggered H ∞ state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays (134 citations)
- Projection models for multiple attribute decision making with picture fuzzy information (132 citations)
What are the main themes of his work throughout his whole career to date?
Fuad E. Alsaadi mostly deals with Control theory, Artificial neural network, Nonlinear system, Estimator and Stochastic process.
Control theory connects with themes related to Bounded function in his study.
His Artificial neural network research focuses on Equilibrium point and how it connects with Uniqueness.
His Nonlinear system study integrates concerns from other disciplines, such as Filtering problem and Mathematical optimization.
Fuad E. Alsaadi combines subjects such as Matrix, State, Discrete time and continuous time, State and Complex network with his study of Estimator.
Fuad E. Alsaadi focuses mostly in the field of Exponential stability, narrowing it down to matters related to Applied mathematics and, in some cases, Stability.
He most often published in these fields:
- Control theory (50.77%)
- Artificial neural network (24.49%)
- Nonlinear system (22.96%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (50.77%)
- Nonlinear system (22.96%)
- Artificial neural network (24.49%)
In recent papers he was focusing on the following fields of study:
Fuad E. Alsaadi mainly focuses on Control theory, Nonlinear system, Artificial neural network, Estimator and Matrix.
His studies deal with areas such as State, Bounded function and Event triggered as well as Control theory.
His Nonlinear system research includes elements of Likelihood function, Energy, Multi-agent system and Transmission.
He has included themes like Stability, Estimation, Quaternion and Order in his Artificial neural network study.
The concepts of his Estimator study are interwoven with issues in Sampling, Algorithm, State and Discrete time and continuous time.
His Matrix research includes themes of Exponential growth and Lyapunov function.
Between 2019 and 2021, his most popular works were:
- Fusion Estimation for Multi-Rate Linear Repetitive Processes under Weighted Try-Once-Discard Protocol (48 citations)
- Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip (34 citations)
- Detection of intermittent faults for nonuniformly sampled multi-rate systems with dynamic quantisation and missing measurements (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Mathematical analysis
Fuad E. Alsaadi spends much of his time researching Control theory, Estimator, Matrix, Mathematical optimization and Artificial neural network.
His studies deal with areas such as Upper and lower bounds, State and Bounded function as well as Control theory.
His Estimator study incorporates themes from Discrete time and continuous time, Exponential stability, State, Sampling and Symmetric matrix.
The Matrix study combines topics in areas such as Exponential growth and Lyapunov function.
Fuad E. Alsaadi has researched Mathematical optimization in several fields, including Computational intelligence, Consensus, Multi-agent system, Benchmark and Eigenvalues and eigenvectors.
His Artificial neural network research is multidisciplinary, incorporating elements of Stability and Estimation.
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