Papers by Madhusudan Singh
IEEE Conference on Cybernetics and Intelligent Systems, 2004.
... JRP Gupta M. Wanmandlu NSIT, New Delhi IIT, Delhi function. But in practical statistical-base... more ... JRP Gupta M. Wanmandlu NSIT, New Delhi IIT, Delhi function. But in practical statistical-based design, we need to capture more probabilistic uncertainties. ... 190-198, 1995. [6] Nilesh N. Kamik,Jerry M. Mendel and Qilian Liang, "Type-2 Fuzzy Logic Systems", IEEE Trms. ...
… (HTTP://WWW. IJCC. …, 2008
Abstract In this paper, the Choquet Integral is used to replace the consequent part of a fuzzy r... more Abstract In this paper, the Choquet Integral is used to replace the consequent part of a fuzzy rule to make the resulting fuzzy system non-additive and type-2 fuzzy sets are used in the antecedent part of the rule to account for varying uncertainties and vagueness. As the stability of the ...
Applied Soft Computing, 2008
For dealing with the adjacent input fuzzy sets having overlapping information, non-additive fuzzy... more For dealing with the adjacent input fuzzy sets having overlapping information, non-additive fuzzy rules are formulated by defining their consequent as the product of weighted input and a fuzzy measure. With the weighted input, need arises for the corresponding fuzzy measure. This is a new concept that facilitates the evolution of new fuzzy modeling. The fuzzy measures aggregate the information from the weighted inputs using the λ-measure. The output of these rules is in the form of the Choquet fuzzy integral. The underlying non-additive fuzzy model is investigated for identification of non-linear systems. The weighted input which is the additive S-norm of the inputs and their membership functions provides the strength of the rules and fuzzy densities required to compute fuzzy measures subject to q-measure are the unknown functions to be estimated. The use of q-measure is a powerful way of simplifying the computation of λ-measure that takes account of the interaction between the weighted inputs. Two applications ; one real life application on signature verification and forgery detection, and another benchmark problem of a chemical plant illustrate the utility of the proposed approach. The results are compared with those existing in the literature.
Applied Soft Computing, 2009
We propose a novel method for the identification of non-linear system by utilizing some of the im... more We propose a novel method for the identification of non-linear system by utilizing some of the important properties of wavelets like denoising, compression, multiresolution along with the concepts of fuzzy logic. Two new type-2 fuzzy wavelet networks (T2FWNs) are proposed here. ...
International Journal of Biomedical Engineering and Technology, 2007
In this paper, a new control algorithm is developed, which uses type-2 fuzzy sets for automatic i... more In this paper, a new control algorithm is developed, which uses type-2 fuzzy sets for automatic insulin delivery rate. Type-2 fuzzy sets have been used to handle uncertainties in the rules due to the inability of type-1 fuzzy sets in such cases. As the stability of the model is also highly dependent on the learning of the system, we have used Lyapunov Stability (LS) in combination with Fuzzy Differential (FD) for learning. A measure of the performance of different controllers is taken by incorporating parametric uncertainty into the model. The effectiveness of the proposed controller is demonstrated on type I diabetes patient.
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Papers by Madhusudan Singh