The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for every used kernel function. Restricted methods to extract rules from SVMs have been previously published. Their limitations are surpassed with the presented extraction method. The behavior of SVMs is explained by means of ...

Steroid receptor activity can be more quickly estimated by size-exclusion chromatography than by conventional analysis on sucrose gradients, and profiles of receptor activity are better resolved. Here we discuss several factors affecting this form of analysis in clinical laboratories. The composition of the elution buffer influences steroid receptor elution and recovery: high ionic strength, ne...

This paper proposes an adaptive TSK-type fuzzy network control (ATFNC) system for synchronization of a coupled nonlinear chaotic system. The design of the proposed ATFNC system is comprised of a neural controller and a fuzzy compensator. The neural controller uses a Takagi-Sugeno-Kang (TSK)-type fuzzy neural network (TFNN) to online mimic an ideal controller and the fuzzy compensator is designe...

In this work the physical-chemical properties of asphaltene-resin-paraffin deposits are studied. Their component composition was determined. The results obtained basis for selection effective solvents and choice method removing from oil reservoirs. Two hydrocarbon with brands “TSK А” B” were tested. solvent ability

The application of conjunctive aggregation operators in fuzzy control systems with 2 inputs is discussed and the effect of the choice of a continuous t-norm operator in inference phase for TSK systems is computed. It is shown that the choice of a continuous t-norm modelling AND connective in antecedent part of fuzzy rules can be reduced just to strict or nilpotent t-norm. Moreover, it is shown ...

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple ov...

One of the best examples of mathematically rigorous signal processing in finance is the Black-Scholes model for price evolution of financial options. To address the same problem, this paper proposes a Takagi-SugenoKang (TSK) fuzzy rule-based option pricing model that requires only a small number of rules to describe highly complex financial signals such as option prices. The findings for this d...

The conventional procedure for the purification of the high affinity K+ uptake ATPase (KdpABC) from Escherichia coli involves a tedious three-column protocol (final enzyme purity, approximately 90%; activity yield, 6.5% (Siebers, A., and Altendorf, K. (1988) Eur. J. Biochem. 178, 131-140)). We have now developed a highly effective one-column (Fractogel TSK AF-Red) protocol yielding an enzyme pr...

This paper presents the application of nonlinear channel equalizers, based on fuzzy IF-THEN rules, for Global System for Mobile (GSM) communication applications. Two types of fuzzy filters namely Type–1 TSK (Takagi – Sugeno – Kang) fuzzy adaptive filter (FAF) and Type–2 TSK FAF are considered for performance comparison. The equalizers proposed can be trained with very short training signal of 2...

Several methodologies for function approximation using TSK systems make use of clustering techniques to place the rules in the input space. Nevertheless classical clustering algorithms are more related to unsupervised learning and thus the output of the training data is not taken into account or, simply the characteristics of the function approximation problem are not considered. In this paper ...