63,701 research outputs found
On Some Linear and Non-linear Fuzzy Integral Equations by Homotopy Perturbation Method
Many mathematical models are contributed to give rise to of linear and nonlinear integral equations. In this paper, we study the performance of recently developed technique homotopy perturbation method by implement on various types of linear and non-linear fuzzy Volterra integral equations of second kind, mixed fuzzy volterra fredholm integral equation and singular fuzzy integral equations. Obtained results show that technique is reliable, efficient and easy to use through recursive relations that involve integrals. Moreover, these particular examples show the reliability and the performance of proposed modifications. Keywords: Homotopy perturbation method, linear fuzzy integral equations, non-linear fuzzy integral equations
Classical Control, Quantum Circuits and Linear Logic in Enriched Category Theory
We describe categorical models of a circuit-based (quantum) functional
programming language. We show that enriched categories play a crucial role.
Following earlier work on QWire by Paykin et al., we consider both a simple
first-order linear language for circuits, and a more powerful host language,
such that the circuit language is embedded inside the host language. Our
categorical semantics for the host language is standard, and involves cartesian
closed categories and monads. We interpret the circuit language not in an
ordinary category, but in a category that is enriched in the host category. We
show that this structure is also related to linear/non-linear models. As an
extended example, we recall an earlier result that the category of W*-algebras
is dcpo-enriched, and we use this model to extend the circuit language with
some recursive types
Equilibria, Fixed Points, and Complexity Classes
Many models from a variety of areas involve the computation of an equilibrium
or fixed point of some kind. Examples include Nash equilibria in games; market
equilibria; computing optimal strategies and the values of competitive games
(stochastic and other games); stable configurations of neural networks;
analysing basic stochastic models for evolution like branching processes and
for language like stochastic context-free grammars; and models that incorporate
the basic primitives of probability and recursion like recursive Markov chains.
It is not known whether these problems can be solved in polynomial time. There
are certain common computational principles underlying different types of
equilibria, which are captured by the complexity classes PLS, PPAD, and FIXP.
Representative complete problems for these classes are respectively, pure Nash
equilibria in games where they are guaranteed to exist, (mixed) Nash equilibria
in 2-player normal form games, and (mixed) Nash equilibria in normal form games
with 3 (or more) players. This paper reviews the underlying computational
principles and the corresponding classes
Polytool: polynomial interpretations as a basis for termination analysis of Logic programs
Our goal is to study the feasibility of porting termination analysis
techniques developed for one programming paradigm to another paradigm. In this
paper, we show how to adapt termination analysis techniques based on polynomial
interpretations - very well known in the context of term rewrite systems (TRSs)
- to obtain new (non-transformational) ter- mination analysis techniques for
definite logic programs (LPs). This leads to an approach that can be seen as a
direct generalization of the traditional techniques in termination analysis of
LPs, where linear norms and level mappings are used. Our extension general-
izes these to arbitrary polynomials. We extend a number of standard concepts
and results on termination analysis to the context of polynomial
interpretations. We also propose a constraint-based approach for automatically
generating polynomial interpretations that satisfy the termination conditions.
Based on this approach, we implemented a new tool, called Polytool, for
automatic termination analysis of LPs
Linear Haskell: practical linearity in a higher-order polymorphic language
Linear type systems have a long and storied history, but not a clear path
forward to integrate with existing languages such as OCaml or Haskell. In this
paper, we study a linear type system designed with two crucial properties in
mind: backwards-compatibility and code reuse across linear and non-linear users
of a library. Only then can the benefits of linear types permeate conventional
functional programming. Rather than bifurcate types into linear and non-linear
counterparts, we instead attach linearity to function arrows. Linear functions
can receive inputs from linearly-bound values, but can also operate over
unrestricted, regular values.
To demonstrate the efficacy of our linear type system - both how easy it can
be integrated in an existing language implementation and how streamlined it
makes it to write programs with linear types - we implemented our type system
in GHC, the leading Haskell compiler, and demonstrate two kinds of applications
of linear types: mutable data with pure interfaces; and enforcing protocols in
I/O-performing functions
Recent advances on recursive filtering and sliding mode design for networked nonlinear stochastic systems: A survey
Copyright © 2013 Jun Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61329301, 61333012, 61374127 and 11301118, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant no. GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Graphical modelling of multivariate time series
We introduce graphical time series models for the analysis of dynamic
relationships among variables in multivariate time series. The modelling
approach is based on the notion of strong Granger causality and can be applied
to time series with non-linear dependencies. The models are derived from
ordinary time series models by imposing constraints that are encoded by mixed
graphs. In these graphs each component series is represented by a single vertex
and directed edges indicate possible Granger-causal relationships between
variables while undirected edges are used to map the contemporaneous dependence
structure. We introduce various notions of Granger-causal Markov properties and
discuss the relationships among them and to other Markov properties that can be
applied in this context.Comment: 33 pages, 7 figures, to appear in Probability Theory and Related
Field
- …