fuzzy reasoning approach. Defuzzifier transforms the inference engine fuzzy outputs into thereal numberdomain of the nonfuzzy output. A corresponding adaptive neural network is designed to integrate the ability to learn from datasets in input and output in fuzzy inference systems. A multilayerfeed...
However, in case of dynamic changes in the parameters of the controlled system, conventionally tuned PID controllers do not show to be robust enough, thus suggesting that fuzzy logic based PIDs are definitively more reliable and effective.Igor S Nadezhdin...
The exploration/exploitation trade-off is a difficult problem for a reinforcement learning agent. A non-stationary environment coupled with current connectionist implementations of reinforcement learning algorithms is a recipe for disaster. Towards a solution for such situations we introduce a novel techniqu...
As the grey model can depict linearity characteristics of network traffic and the BP neural network model can depict the non-stationary and non-linear characteristics, a Fuzzy Self-Adaptive Variable-Weight Combination Prediction Model (FSVCPM) was composed of them. To improve the prediction accuracy...
Two adaptive fuzzy-neural control schemes within the indirect and direct frameworks suppressing the wing rock are proposed in [30]. A fuzzy neural network (FNN) with any bounded non-constant piecewise continuous membership function is used to approximate the system nonlinear dynamics and external dist...
In this study, the integration of an adaptive hybrid of differential evolution and particle swarm optimization (A-DEPSO) with adaptive neuro fuzzy inference system (ANFIS) model is adopted for EC prediction. The A-DEPSO method uses unique mutation and crossover processes to correspondingly boost ...
neural networks; stochastic systems; nonstationary noise; distribution modelling; 71.Exploiting all combinations of microphone sensors in overdetermined frequency domain blind separation of speech signals 机译:在超频域语音信号盲分离中利用麦克风传感器的所有组合 作者:Yonggang Zhang;Jonathon A. Chambers...
The network plasticity obeys the Hebbian rule60 and involves only excitatory-excitatory connections. The model parameters (see Methods) are set to values that correspond to the emergence of a stationary regime for the dynamics of an isolated node, i.e., the excitatory and inhibitory population ...
Researchers at Shanghai University of Engineering Science Release New Data on Networks (Event-triggered Adaptive Neural Network Backstepping Sliding Mode Control... - 《Network Daily News》 被引量: 0发表: 2023年 Solving Nonstationary Classification Problems With Coupled Support Vector Machines Many learn...
We present convergence theorems for both of our algorithms drawing on the theory of non-stationary and stationary discrete-time Markov chains over the reals. We present an extensive empirical evaluation of our algorithms on a simulator that is widely used in the computer networks community for ...