Results 251 to 260 of about 11,089,487 (322)
Optimized Fractional-Order Extended Kalman Filtering for IMU-Based Attitude Estimation Using the Hippopotamus Algorithm. [PDF]
Yang X +5 more
europepmc +1 more source
A qualitative study on the stability and existence of solutions in a fractional-order water pollution model via the predictor-corrector approach. [PDF]
Iqbal N +3 more
europepmc +1 more source
Adaptive fractional-order non-singular terminal sliding mode control for omnidirectional quadrotors based on WRBF neural network. [PDF]
Ma R, Gu Q, Ding L, Li Y, Sun C, Wu H.
europepmc +1 more source
Fractional order tracking control of a disturbed differential mobile robot. [PDF]
Aguilar-Pérez JI +3 more
europepmc +1 more source
A statistical estimation of fractional order cryptosporidiosis epidemic model. [PDF]
Ahmed N +10 more
europepmc +1 more source
Numerical study on fractional order nonlinear SIR-SI model for dengue fever epidemics. [PDF]
Verma L, Meher R, Nikan O, Al-Saedi AA.
europepmc +1 more source
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IEEE Transactions on Cybernetics, 2020
This paper investigates exponential stability of fractional-order impulsive control systems (FICSs) and exponential synchronization of fractional-order Cohen–Grossberg neural networks (FCGNNs).
Cheng Hu, Haijun Jiang, Cheng Hu
exaly +2 more sources
This paper investigates exponential stability of fractional-order impulsive control systems (FICSs) and exponential synchronization of fractional-order Cohen–Grossberg neural networks (FCGNNs).
Cheng Hu, Haijun Jiang, Cheng Hu
exaly +2 more sources
IEEE Transactions on Cybernetics, 2020
In this paper, spatial diffusions are introduced to fractional-order coupled networks and the problem of synchronization is investigated for fractional-order coupled neural networks with reaction-diffusion terms.
Cheng Hu, Haijun Jiang, Tingwen Huang
exaly +2 more sources
In this paper, spatial diffusions are introduced to fractional-order coupled networks and the problem of synchronization is investigated for fractional-order coupled neural networks with reaction-diffusion terms.
Cheng Hu, Haijun Jiang, Tingwen Huang
exaly +2 more sources
Neural Networks, 2023
Fractional-order differentiation (FOD) can record information from the past, present, and future. Compared with integer-order systems, FOD systems have higher complexity and more accurate ability to describe the real world.
Xinxin Kong +5 more
semanticscholar +1 more source
Fractional-order differentiation (FOD) can record information from the past, present, and future. Compared with integer-order systems, FOD systems have higher complexity and more accurate ability to describe the real world.
Xinxin Kong +5 more
semanticscholar +1 more source

