State estimation for discrete-time delayed neural networks with fractional uncertainties and sensor saturations

Neurocomputing

Volumn 117, Issue , 2013, Pages 64-71

  Kan, Xiu ^a   Wang, Zidong ^a,b   Shu, Huisheng ^a  

^a DONGHUA UNIVERSITY   (China)

^b BRUNEL UNIVERSITY   (United Kingdom)

Author keywords

Exponential stability; Fractional uncertainty; Neural networks; Sensor saturation; State estimation; Time varying delays

Indexed keywords

DELAYED NEURAL NETWORKS; ESTIMATION APPROACHES; FRACTIONAL UNCERTAINTY; GLOBALLY EXPONENTIALLY STABLE; PARAMETER UNCERTAINTY; SENSOR SATURATIONS; TIME-VARYING DELAY; UNCERTAINTY STRUCTURE;

ASYMPTOTIC STABILITY; ESTIMATION; NEURAL NETWORKS; PHASE BEHAVIOR; SENSORS;

STATE ESTIMATION;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLINICAL EFFECTIVENESS; FRACTIONAL UNCERTAINTY; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MEASUREMENT ERROR; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; SENSOR SATURATION; SYSTEMATIC ERROR;

EID: 84878896811     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.01.039     Document Type: Article

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