Distributed Approximating Functional Networks
نویسندگان
چکیده
We present a novel polynomial functional neural networks using Distributed Approximating Functional (DAF) wavelets (infinitely smooth filters in both time and frequency regimes), for signal estimation and surface fitting. The remarkable advantage of these polynomial nets is that the functional space smoothness is identical to the state space smoothness (consisting of the weighting vectors). The constrained cost energy function using optimal regularization programming endows the networks with a natural time-varying filtering feature. Theoretical analysis and an application show that the approach is extremely stable and efficient for signal processing and curve/surface fitting.
منابع مشابه
Lagrange-distributed approximating-functional approach to wave-packet propagation: Application to the time-independent wave-packet reactant-product decoupling method
A connection is made between a recently introduced Lagrange-distributed approximating-functional and the Paley-Wiener sampling theorem. The Lagrange-distributed approximating-functional sampling is found to provide much superior results to that of Paley-Wiener sampling. The relations between discrete variable representation and Lagrange-distributed approximating functionals are discussed. The l...
متن کاملLinear matrix inequality approach for synchronization of chaotic fuzzy cellular neural networks with discrete and unbounded distributed delays based on sampled-data control
In this paper, linear matrix inequality (LMI) approach for synchronization of chaotic fuzzy cellular neural networks (FCNNs) with discrete and unbounded distributed delays based on sampled-data controlis investigated. Lyapunov-Krasovskii functional combining with the input delay approach as well as the free-weighting matrix approach are employed to derive several sufficient criteria in terms of...
متن کاملBiomedical Signal Processing Using DAF Networks
Distributed Approximating Functional (DAF) neural networks are presented for biomedical signal processing. The remarkable advantage of such net is that the functional space smoothness is identical to the state space smoothness (consisting of the weighting vectors). The constrained cost energy function using the regularization programming endows a natural time-varying filtering. Theoretical anal...
متن کاملRobust stability of fuzzy Markov type Cohen-Grossberg neural networks by delay decomposition approach
In this paper, we investigate the delay-dependent robust stability of fuzzy Cohen-Grossberg neural networks with Markovian jumping parameter and mixed time varying delays by delay decomposition method. A new Lyapunov-Krasovskii functional (LKF) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matr...
متن کاملDistributed approximating functional approach to the Fokker–Planck equation: Time propagation
The Fokker–Planck equation is solved by the method of distributed approximating functionals via forward time propagation. Numerical schemes involving higher-order terms in Dt are discussed for the time discretization. Three typical examples ~a Wiener process, an Ornstein–Uhlenbeck process, and a bistable diffusion model! are used to test the accuracy and reliability of the present approach, whi...
متن کامل