We introduce a type-2 fuzzy logic system (FLS), which can handle rule uncertainties. The implementation of this type-2 FLS involves the operations of fuzzification, inference, and output processing. We focus on "output processing," which consists of type reduction and defuzzification. Type-reduction methods are extended versions of type-1 defuzzification methods. Type reduction captures more information about rule uncertainties than does the defuzzified value (a crisp number), however, it is computationally intensive, except for interval type-2 fuzzy sets for which we provide a simple type-reduction computation procedure. We also apply a type-2 FLS to time-varying channel equalization and demonstrate that it provides better performance than a type-1 FLS and nearest neighbor classifier.

No abstract

In this paper, we present the theory and design of interval type-2 fuzzy logic systems (FLSs). We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs; one that is based on a general inference formula for them. We introduce the concept of upper and lower membership functions (MFs) and illustrate our efficient inference method for the case of Gaussian primary MFs. We also propose a method for designing an interval type-2 FLS in which we tune its parameters. Finally, we design type-2 FLSs to perform time-series forecasting when a nonstationary time-series is corrupted by additive noise where SNR is uncertain and demonstrate improved performance over type-1 FLSs. Index Terms-Interval type-2 fuzzy sets, nonsingleton fuzzy logic systems, time-series forecasting, tuning of parameters, type-2 fuzzy logic systems, upper and lower membership functions.

Motivated by the observation that channel assignment for multiradio multi-channel mesh networks should support both unicast and local broadcast 1 , should be interference-aware, and should result in low overall switching delay, high throughput, and low overhead, we propose two flexible localized channel assignment algorithms based on s-disjunct superimposed codes. These algorithms support the local broadcast and unicast effectively, and achieve interference-free channel assignment under certain conditions. In addition, under the primary interference constraints 2 , the channel assignment algorithm for unicast can achieve 100% throughput with a simple scheduling algorithm such as the maximal weight independent set scheduling, and can completely avoid hidden/exposed terminal problems under certain conditions. Our algorithms make no assumptions on the underlying network and therefore are applicable to a wide range of MR-MC mesh network settings. We conduct extensive theoretical performance analysis to verify our design.

No abstract

In this article, we discuss techniques for sense through wall human detection for different types of walls. We have focused on detection of stationary human target behind wall based on breathing movements. In detecting the breathing motion, a Doppler based method is used. Also a new approach based on short time Fourier transform is discussed and an already proposed clutter reduction technique based on singular value decomposition is applied to different measurements.

No abstract

No abstract