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This paper addresses the

In recent years, the control and filtering problems for Takagi-Sugeno (T-S) fuzzy systems, which have been employed to solve a great deal of issues in control and filtering fields, have drawn a great attention of many researchers [

On the other hand, a large number of practical engineering problems encounter time-delay phenomenon, which is always a source of poor performance and even instability of the systems [

In practical engineering, sensor saturation is one of the most popular phenomena that limits the performance of sensors on various aspects significantly. When sensors cannot provide the enough amplitude signals due to the physical or safety constraints [

Motivated by the above reasons, we investigate the

The remainder of this paper is organized as follows. In Section

We consider the following nonlinear fuzzy dynamic described by a Takagi-Sugeno (T-S) stochastic model:

In the system (

The exogenous disturbance

The defuzzified output of the T-S fuzzy system (

In this paper, the sensor saturation is described by the saturation function

For the fuzzy system (

Define the following error variables:

Furthermore, the following definitions will be used in this paper.

For the system in (

A mapping

Then, the main objective of this paper is as follows.

In this section, we focus on the filter performance analysis based on the developed SSG theorem. By the developed SSG theorem to the stochastic systems and a new model transformation to the system

Consider the following interconnected system consisting of two subsystems in Figure

The interconnection subsystems.

Considering (

Consider the system described in (

The proof of Corollary

To transform the systems (

Furthermore, the SSG of the mapping

According to the fact that

From Lemmas

In this section, the

Suppose that the system matrices

Choose the following Lyapunov-Krasovskii functional:

Define

Then, define

Furthermore,

Theorem

For the forward system

For the LKF defined in (

Define

For any positive integer

It is well known that free-weighting matrices are introduced a lot to estimate the upper bound of the term

This section is devoted to the

Consider the discrete-time fuzzy stochastic system in (

Define

Then, we have

In this section, an example is provided to demonstrate effectiveness of the filter design method proposed in the preceding sections.

Consider the system (

To design the

Assume the sensor saturation as

This paper addresses the

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_{∞}synchronization for uncertain neural networks with mixed time delays

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