Search results for "Intelligence"
showing 10 items of 6959 documents
The expressive power of the shuffle product
2010
International audience; There is an increasing interest in the shuffle product on formal languages, mainly because it is a standard tool for modeling process algebras. It still remains a mysterious operation on regular languages.Antonio Restivo proposed as a challenge to characterize the smallest class of languages containing the singletons and closed under Boolean operations, product and shuffle. This problem is still widely open, but we present some partial results on it. We also study some other smaller classes, including the smallest class containing the languages composed of a single word of length 2 which is closed under Boolean operations and shuffle by a letter (resp. shuffle by a l…
Fast Matrix Multiplication
2015
Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time O(n2.3755). Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le~Gall has led to an improved algorithm running in time O(n2.3729). These algorithms are obtained by analyzing higher and higher tensor powers of a certain identity of Coppersmith and Winograd. We show that this exact approach cannot result in an algorithm with running time O(n2.3725), and identify a wide class of variants of this approach which cannot result in an algorithm with running time $O(n^{2.3078}); in particular, this approach cannot prove the conjecture that for every e > 0, …
On a class of languages with holonomic generating functions
2017
We define a class of languages (RCM) obtained by considering Regular languages, linear Constraints on the number of occurrences of symbols and Morphisms. The class RCM presents some interesting closure properties, and contains languages with holonomic generating functions. As a matter of fact, RCM is related to one-way 1-reversal bounded k-counter machines and also to Parikh automata on letters. Indeed, RCM is contained in L-NFCM but not in L-DFCM, and strictly includes L-CPA. We conjecture that L-DFCM subset of RCM
Filtering design for two-dimensional Markovian jump systems with state-delays and deficient mode information
2014
This paper is concerned with the problem of H"~ filtering for a class of two-dimensional Markovian jump linear systems described by the Fornasini-Marchesini local state-space model. The systems under consideration are subject to state-delays and deficient mode information in the Markov chain. The description of deficient mode information is comprehensive that simultaneously includes the exactly known, partially unknown and uncertain transition probabilities. By invoking the properties of the transition probability matrix, together with the convexification of uncertain domains, a new H"~ performance analysis criterion for the filtering error system is firstly derived. Then, via some matrix i…
Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis
2022
Random mechanisms including mutations are an internal part of evolutionary algorithms, which are based on the fundamental ideas of Darwin's theory of evolution as well as Mendel's theory of genetic heritage. In this paper, we debate whether pseudo-random processes are needed for evolutionary algorithms or whether deterministic chaos, which is not a random process, can be suitably used instead. Specifically, we compare the performance of 10 evolutionary algorithms driven by chaotic dynamics and pseudo-random number generators using chaotic processes as a comparative study. In this study, the logistic equation is employed for generating periodical sequences of different lengths, which are use…
Ordinal mind change complexity of language identification
1997
The approach of ordinal mind change complexity, introduced by Freivalds and Smith, uses constructive ordinals to bound the number of mind changes made by a learning machine. This approach provides a measure of the extent to which a learning machine has to keep revising its estimate of the number of mind changes it will make before converging to a correct hypothesis for languages in the class being learned. Recently, this measure, which also suggests the difficulty of learning a class of languages, has been used to analyze the learnability of rich classes of languages. Jain and Sharma have shown that the ordinal mind change complexity for identification from positive data of languages formed…
Model approximation for two-dimensional Markovian jump systems with state-delays and imperfect mode information
2014
Published version of an article in the journal: Multidimensional Systems and Signal Processing. Also available from the publisher at: http://dx.doi.org/10.1007/s11045-013-0276-x This paper is concerned with the problem of {Mathematical expression} model approximation for a class of two-dimensional (2-D) discrete-time Markovian jump linear systems with state-delays and imperfect mode information. The 2-D system is described by the well-known Fornasini-Marchesini local state-space model, and the imperfect mode information in the Markov chain simultaneously involves the exactly known, partially unknown and uncertain transition probabilities. By using the characteristics of the transition proba…
The arithmetic decomposition of central Cantor sets
2018
Abstract Every central Cantor set of positive Lebesgue measure is the arithmetic sum of two central Cantor sets of Lebesgue measure zero. Under some mild condition this result can be strengthened by stating that the summands can be chosen to be C s regular if the initial set is of this class.
Stability of genetic regulatory networks with time-varying delay: Delta operator method
2015
This paper investigates the stability problem for a class of uncertain genetic regulatory networks (GRNs) with time-varying delay via delta operator approach. Both the parameter uncertainty and the generalized activations are considered in the model under study. By constructing an appropriate Lyapunov-Krasovskii functional, the stability and robust stability conditions of GRNs are presented under the delta operator frame. These conditions can be expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is employed to illustrate the effectiveness of the proposed results.
Pattern classification using a new border identification paradigm: The nearest border technique
2015
Abstract There are many paradigms for pattern classification such as the optimal Bayesian, kernel-based methods, inter-class border identification schemes, nearest neighbor methods, nearest centroid methods, among others. As opposed to these, this paper pioneers a new paradigm, which we shall refer to as the nearest border (NB) paradigm. The philosophy for developing such a NB strategy is as follows: given the training data set for each class, we shall attempt to create borders for each individual class. However, unlike the traditional border identification (BI) methods, we do not undertake this by using inter-class criteria; rather, we attempt to obtain the border for a specific class in t…