It is traditional to initialise Kalman filters and extended Kalman filters with estimates of the states calculated directly from the observed (raw) noisy inputs7, 9, 10 but unfortunately their performance is extremely sensitive to state initialisation accuracy (Figure 1). Good initial state estimates ensure fast convergence whereas poor estimates may give rise to slow convergence or even filter...

Phenomenological theory of mind based on simple concepts related to human cognition is introduced. Basic concepts of this theory are directly related to neurophysiological events in the brain and may also be extended to explain higher cognitive functions realized by the mind. This theory on the one hand solves fundamental problems in cognitive sciences, explaining puzzling behavior of human con...

In this paper, a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective. Such a compensatory fuzzy logic system is proved to be a universal approximator. The compensatory neural fuzzy networks built by both control-oriented fuzzy neurons and decision-oriented fuzzy neurons cannot only adaptively adjust fuz...

In this paper a novel neural fuzzy inference network (NFIN) it is proposed. The NFIN represent a modified Takagi-Sugeno-Kang (TSK) type fuzzy rule based model with neural network learning ability. The rules in the NFIN are created and adapted in an on-line learning algorithm. The structure learning together with the parameter learning forms the learning algorithms for the neural fuzzy network. ...

In this paper we propose a dynamic evolving neuro-fuzzy inference system (DENFIS) to forecast mortality. DENFIS is an adaptive intelligent system suitable for dynamic time series prediction. An Evolving Cluster Method (ECM) drives the learning process. The typical fuzzy rules of the neurofuzzy systems are updated during the learning process and adjusted according to the features of the data. Th...

This paper addresses the issue of controlling nonlinear processes by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a neuro-fuzzy process model is suggested as a means to model processes with strong nonlinearities depending on the operating region. In this paper the neurofuzzy approach is used for the modelling and control of a strongly nonlinear pH...

This paper reports application of neurofuzzy inference system (NFIS) and self organizing feature map neural networks (SOM) on detection of contact state in a block system. In this manner, on a simple system, the evolution of contact states, by parallelization of DDA, has been investigated. So, a comparison between NFIS and SOM results has been presented. The results show applicability of the pr...

The article is devoted to the issue of creating a mathematical model problem making management decisions in electric power facilities based on modern intelligent technologies, which makes it possible take into account influence various factors operating modes system. A systematic approach describing processes language theory fuzzy sets proposed. To solve controlling system, neurofuzzy network h...