Mohammad Reza Rajati

• PhD in Electrical Engineering
• Lecturer at University of Southern California

In this paper, we extend the concept of Dempster-Shafer Belief Structures to the case of Linguistic Belief Structures, whose focal elements and probability mass assignments are linguistic, i.e. words modeled by Interval Type-2 Fuzzy Sets. We show that Linguistic Weighted Averages are pertinent tools for derivation of lower and upper probabilities f...

WordNet lexical-database groups English words into sets of synonyms called "synsets." Synsets are utilized for several applications in the field of text-mining. However, they were also open to criticism because although, in reality, not all the members of a synset represent the meaning of that synset with the same degree, in practice, they are cons...

Deep neural networks have achieved great success in classification tasks during the last years. However, one major problem to the path towards artificial intelligence is the inability of neural networks to accurately detect samples from novel class distributions and therefore, most of the existent classification algorithms assume that all classes a...

Deep neural networks are known to achieve superior results in classification tasks. However, it has been recently shown that they are incapable to detect examples that are generated by a distribution which is different than the one they have been trained on since they are making overconfident prediction for Out-Of-Distribution (OOD) examples. OOD d...

Deep neural networks have achieved great success in classification tasks during the last years. However, one major problem to the path towards artificial intelligence is the inability of neural networks to accurately detect samples from novel class distributions and therefore, most of the existent classification algorithms assume that all classes a...

In this article, we utilize an Extension Principle for set-to-point functions to calculate fuzzy-valued belief and plausibility for a fuzzy hypothesis from a fuzzy belief structure based on decomposing the fuzzy hypothesis into its α-cuts and inferring the belief and the plausibility of each α-cut from the belief structure. Aggregating belief and p...

Soft Decision Trees have been proven to have better performance in terms of accuracy and complexity compared to conventional Decision Trees. Nevertheless, they do not possess inherent explanation capability to interpret the learning process of which the conventional Decision Trees are capable because a Soft Decision Tree redirects instances to all...

This paper is about some important type-2 fuzzy set (T2 FS) notational changes that have occurred during the past 16 years. It summarizes the evolution of how the primary membership (Jx) has been used in both the mathematical descriptions of a T2 FS and its footprint of uncertainty (FOU); discusses notational problems associated with the secondary...

WordNet-like Lexical Databases (WLDs) group English words into synsets, being utilized in several text mining applications. Synsets were also open to criticism, because while synset members (wordsenses) are, in practice, considered as compeers, yet in theory not all of them represent the synset meaning with a same degree. Considering this criticism...

In this paper, we consider an improved and efficient algorithm for the multiuser detection (MUD) in direct sequence/code division multiple access (DS/CDMA) communication systems. The optimum detector for MUD is the maximum likelihood (ML) detector, but its complexity is very high and it calls for an optimization problem that involves an exhaustive...

In this chapter, we focus on the status of Advanced Computing with Words (ACWW) and the challenges that it may encounter in the future. First, we elaborate on the notion of Computing with Words (CWW) and its various subareas. Then we present some non-engineering ACWW problems and connect them to more realistic engineering problems, after which we p...

In this paper, we present a data driven methodology for designing a decision support system for controlling the choke setting in a Cyclic Steam Stimulation (CSS) system based on fuzzy logic. The goal of the fuzzy decision system is to find a choke setting that enhances the amount of liquid offload in different situations and therefore, the producti...

In this Letter we provide some critiques of the 2014 Information Sciences paper by Mo, et al. [9], and point out and correct six erroneous statements and false impressions that have been made in this paper.

In this paper, we propose and demonstrate an effective methodology for implementing the generalized extension principle to solve Advanced Computing with Words (ACWW) problems. Such problems involve implicit assignments of linguistic truth, probability, and possibility. To begin, we establish the vocabularies of the words involved in the problems, a...

This paper explains how to compute normalized interval type-2 fuzzy sets in closed form and explains how the results reduce to well-known results for type-1 fuzzy sets and interval sets. Such normalized interval type-2 fuzzy sets may be needed in linguistic probability computations or multiple criteria decision analysis under uncertainty.

In this paper, we propose a method for extending set functions to Interval Type-2 Fuzzy Sets. We start from the Extension Principle for extending set functions to Type-1 Fuzzy Sets. Then we extend set functions to embedded Type-1 Fuzzy Sets of Interval Type-2 Fuzzy Sets. Consequently, we construct the Interval Type-2 Fuzzy Set result of the extensi...

In this paper, we consider metacognition and self-reference realized in the framework of fuzzy computing. Different aspects of self-reference are discussed from the viewpoint of logic, linguistics, and artificial intelligence. Previous work in the area of fuzzy logic is also revisited in this context. It is shown that the reasoning based on the tru...

In this paper, we present an efficient evolutionary algorithm for Multiuser Detection (MUD) problem in Direct Sequence-Code Division Multiple Access (DS-CDMA) communication systems. The optimum detector for MUD is the Maximum Likelihood (ML) detector, but its complexity is very high and involves an exhaustive search to reach the best fitness of the...

In this paper, we present solutions to an Advanced Computing with Words problem that is equivalent to one of Zadeh's challenge problems on linguistic probabilities. We use a syllogism based on the entailment principle to interpret the problem so that it yields two linguistic belief structures. Then we perform an addition of those linguistic belief...

In this paper, we synthesize interval type-2 fuzzy set models of linguistic probability words and linguistic quantifiers by applying the Enhanced Interval Approach to data collected from subjects about those words. We establish some user friendly sub-vocabularies of linguistic probabilities and linguistic modifiers, so that they can be used in adva...

In this paper, some properties of Novel Weighted Averages that are related to the concepts of possibility theory are examined. It is shown that Novel Weighted Averages have certain interpretations in terms of addition of interactive interval or fuzzy constraints. To do this, alternative forms of Novel Weighted Averages are provided. In particular,...

Modeling real-world systems plays an essential role in system analysis, and contributes to a better understanding of their behavior and performance. Classification, optimization, controls, and pattern recognition problems heavily rely on modeling techniques. From a particular viewpoint, models could be categorized into three classes: white box, bla...

Modeling real-world systems plays an essential role in system analysis, and contributes to a better understanding of their behavior and performance. Classification, optimization, controls, and pattern recognition problems heavily rely on modeling techniques. From a particular viewpoint, models could be categorized into three classes: white box, bla...

In this paper, we present a solution to Zadeh's Swedes and Italians challenge problem which involves linguistic quantifiers and linguistic attributes. First, we argue that Zadeh's solution to this problem via the Generalized Extension Principle is very difficult to implement. Then, we use a syllogism based on the entailment principle to interpret t...

In this paper, we present solutions to Zadeh's challenge problem on calculating linguistic probabilities. First, we argue that Zadeh's solution to this problem via the Generalized Extension Principle is very difficult to implement. Then, we use a syllogism based on the entailment principle to interpret the problem so that it can be solved by calcul...

In this paper, we consider metacognition and self-reference realized in the frame- work of fuzzy computing. Different aspects of self-reference are discussed from the viewpoint of logic, linguistics, and artificial intelligence. Previous work in the area of fuzzy logic is also revisited in this context. It is shown that the reasoning based on the t...

In this paper, we present a solution to Zadeh's Magnus challenge problem on linguistic probabilities. First, we implement Zadeh's solution to this problem. Then, we use the intersection-product syllogism and a syllogism based on the entailment principle to interpret the problem so that it can be solved via Linguistic Weighted Averages. We show that...

The purpose of this paper is to formulate truth-value assignment to self-referential sentences via Zadeh's truth qualification principle and to present new methods to assign truth-values to them. Therefore, based on the truth qualification process, a new interpretation of possibilities and truth-values is suggested by means of type-2 fuzzy sets and...

The aim of this study is to provide an experiment design method for modeling and function approximation. Modeling real-life systems is extremely of interest nowadays. Models could be useful in analysis of systems and help us understand their behavior. From a new point, models could be classified into three classes: black box models, gray box models...

Covariance control theory provides a parameterization of all controllers which assign a specified state covariance matrix to the closed loop system. Our approach deals with the problem of describing a covariance state space model for stochastic systems. We derived the closed-from of the state covariance equations based on the model of the original...

In this paper a Modified Artificial Immune System (MAIS) is presented as a powerful tool for data classification. We discuss how Artificial Immune System (AIS) could classify data inspired by the natural immune systems. Inspired by the interaction between electric charges, some modifications are performed to calculate the Stimulation Level (SL) of...

In this paper a model-free optimization method is applied to the problem of unit sizing in a hybrid power system such that demand of residential area is met. Optimal sizing of two systems is considered. In the system No.l, the produced power is delivered to the load and the hydrogen produced by the reformer is stored in the tank. If the power produ...

This paper presents an accurate method to determine the environment model for decentralized detection in sensor networks. We develop a clustering algorithm to classify sensor data and to achieve this model. Then we further enhance the performance of the method in case of noisy sensors, non- identical observations and unreliable communication links....

In this paper, an improved genetic algorithm is proposed to solve the economic dispatch (ED) problem for co- generation systems. The proposed algorithm is a novel bio-inspired Genetic Algorithm. This algorithm seems to be efficient in finding global optimum in the economic dispatch problem. Furthermore, it provides a suitable framework for future e...

In this paper, relative capacity of a specific higher order Hopfield-type associative memory is considered. This model, which is known as exponential Hopfield neural network is suitable for hardware implementation and is not of a great computational cost. It is shown that, this modification of the Hopfield model significantly improves the storage c...

The purpose of this paper is to formulate truth-value assignment to self-referential sentences via Zadeh's truth qualification principle and to present new methods to assign truth-values to them. Therefore, based on the truth qualification process, a new interpretation of possibilities and truth-values is suggested by means of type-2 fuzzy sets and...

In this paper, we consider the storage capacity and stability of the so-called Hopfield neural networks with higher order nonlinearity. There are different ways to introduce higher order nonlinearity to the network; however we have considered one which does not have a huge computational cost. It is shown that, this modification of the Hopfield mode...

This paper first reviews several learning methods for training Hopfield-type associative memories as well as a novel architecture with neurons of nonmonotonic stimulus functions. These learning rules are classified into three groups according to a measure of stability closely related to the storage capacity. This measure helps us better study the a...

In this paper, we consider the storage capacity and stability of the so-called Hopfield neural networks with higher order nonlinearity. There are different ways to introduce higher order nonlinearity to the network; however we have considered one which does not have a huge computational cost. It is shown that, this modification of the Hopfield mode...