Artificial Neural Network (ANN) based model has been proposed for diagnosis of process mean shift. These are mainly generalized-based where only a single classifier was applied in the diagnosis of abnormal pattern. In this paper, we analyze the performance of a combined recognizer consisting of small-sized artificial neural networks on varying number of nodes in the hidden layer trained with Le...

Previous studies on fuzzy linear regression analysis have a common characteristic of increasing spreads for the estimated fuzzy responses as the independent variable increases its magnitude, which is not suitable for general cases. This paper proposes a two-stage approach to construct the fuzzy linear regression model. In the 2rst stage, the fuzzy observations are defuzzi2ed so that the traditi...

Takagi–Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. Analytical structure of TS fuzzy models, however, is presently unknown, nor is its possible connection with the traditional models, causing at least two major problems. First, the fuzzy models can hardly be utilized to des...

Algebra of ordered fuzzy numbers (OFN) is defined to handle with fuzzy inputs in a quantitative way, exactly in the same way as with real numbers. Additional two structures: algebraic and normed (topological) are introduced to define a general form of defuzzyfication operators. A useful implementation of a Fuzzy Calculator allows counting with the general type membership relations.

Soft set theory was introduced by Molodtsov in 1999 as a general mathematical tool for dealing with problems that contain uncertainty. In this paper, we define concept of fuzzy soft lattice, fuzzy soft sublattice, complete fuzzy soft lattice, modular fuzzy soft lattice, distributive fuzzy soft lattice, fuzzy soft chain and study their basic properties.

A time-varying Wiener filter extracts a speech signal from a mixture using the a priori signal-to-noise ratio in a local time-frequency unit. We estimate this ratio using a binaural processor and derive a ratio time-frequency mask. This mask is used to extract the speech, which is then fed to a conventional speech recognizer operating in the cepstral domain. We compare the performance of this s...

the paper sets forth in detail categorically-algebraic or catalg foundations for the operations of taking the image and preimage of (fuzzy) sets called forward and backward powerset operators. motivated by an open question of s. e. rodabaugh, we construct a monad on the category of sets, the algebras of which generate the fixed-basis forward powerset operator of l. a. zadeh. on the next step, w...

This paper describes the development and implementation of a discrete speech recognizer for application in miniaturized, portable low-power devices. The recognizer is based on Hidden Markov Models (HMMs) and uses Linear Predictive Coefficients (LPC) converted to cepstrum to parameterize the input speech. The implemented recognizer has a complexity of 0.67 MIPS and a recognition performance of 9...