AIMC Topic: Computer Simulation

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Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

Computers in biology and medicine
In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multicl...

Adaptive Neural Output Feedback Control of Output-Constrained Nonlinear Systems With Unknown Output Nonlinearity.

IEEE transactions on neural networks and learning systems
This paper addresses the problem of adaptive neural output-feedback control for a class of special nonlinear systems with the hysteretic output mechanism and the unmeasured states. A modified Bouc-Wen model is first employed to capture the output hys...

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans.

Journal of computational neuroscience
Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous sys...

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words.

Computational intelligence and neuroscience
With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive an...

Initialization by a novel clustering for wavelet neural network as time series predictor.

Computational intelligence and neuroscience
The architecture and parameter initialization of wavelet neural network are discussed and a novel initialization method is proposed. The new approach can be regarded as a dynamic clustering procedure which will derive the neuron number as well as the...

Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study.

Computational intelligence and neuroscience
This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm opti...

Memory dynamics in attractor networks.

Computational intelligence and neuroscience
As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this...

Neural Controller Design-Based Adaptive Control for Nonlinear MIMO Systems With Unknown Hysteresis Inputs.

IEEE transactions on cybernetics
This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of N subsystems in pure feedback structure and the interconnection terms are contained in ever...

Discontinuous Lyapunov approach to state estimation and filtering of jumped systems with sampled-data.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the sampled-data state estimation and H(∞) filtering for a class of Markovian jump systems with the discontinuous Lyapunov approach. The system measurements are sampled and then transmitted to the estimator and filter in ...

Briefing in application of machine learning methods in ion channel prediction.

TheScientificWorldJournal
In cells, ion channels are one of the most important classes of membrane proteins which allow inorganic ions to move across the membrane. A wide range of biological processes are involved and regulated by the opening and closing of ion channels. Ion ...