a comparative evaluation of matlab, octave, freemat - here

... Scilab, and provide information on which package is most compatible to Matlab users. Section 1.3 provides more detailed descriptions of these packages. To evaluate GNU Octave, FreeMat, and Scilab, a comparative approach is used based on a Matlab user’s perspective. To achieve this task, we perform s ...

... Scilab, and provide information on which package is most compatible to Matlab users. Section 1.3 provides more detailed descriptions of these packages. To evaluate GNU Octave, FreeMat, and Scilab, a comparative approach is used based on a Matlab user’s perspective. To achieve this task, we perform s ...

A Comparative Analysis of Different Categorical Data Clustering

... emerged over earlier periods. Conversely it is known that there is no single clustering method is capable of providing accurate and appropriate cluster results [14]. Since by applying a clustering algorithm to the data set it works on the basis of the internal criteria i.e. similarity or dissimilari ...

... emerged over earlier periods. Conversely it is known that there is no single clustering method is capable of providing accurate and appropriate cluster results [14]. Since by applying a clustering algorithm to the data set it works on the basis of the internal criteria i.e. similarity or dissimilari ...

A Review of Recent Developments in Solving ODES

... Although many of the current methods for solving ODES were developed around the turn of the century, the past 15 years or so has been a period of intensive research. The emphasis of this survey is on the methods and techniques used in software for solving ODES. ODES can be classified as stiff or non ...

... Although many of the current methods for solving ODES were developed around the turn of the century, the past 15 years or so has been a period of intensive research. The emphasis of this survey is on the methods and techniques used in software for solving ODES. ODES can be classified as stiff or non ...

08_524 - Bangladesh Mathematical Society

... transformation by which one can transform 1D NSE to 1D Burgers’ equation. The explicit exponential finite difference method has originally developed by Bhattacharya [6] for the solution of heat equation. Bhattacharya [7] used explicit exponential finite difference method for the solution of Burgers’ ...

... transformation by which one can transform 1D NSE to 1D Burgers’ equation. The explicit exponential finite difference method has originally developed by Bhattacharya [6] for the solution of heat equation. Bhattacharya [7] used explicit exponential finite difference method for the solution of Burgers’ ...

Preconditioning of Markov Chain Monte Carlo Simulations Using

... pre-computed multiscale basis functions and solve the saturation on the fine grid. This provides an accurate approximation for the production data [13, 14, 1]. Since one can re-use the basis functions from the first stage, the resulting method is very efficient. We would like to note that upscaled m ...

... pre-computed multiscale basis functions and solve the saturation on the fine grid. This provides an accurate approximation for the production data [13, 14, 1]. Since one can re-use the basis functions from the first stage, the resulting method is very efficient. We would like to note that upscaled m ...

Exact Solution of Time History Response for Dynamic

... with operation count of approximately the cube of the number of retained real modes and is not exact because of the linear approximations. Alternatively, Picard iteration can be used to solve the pseudo-uncoupled equations, see [11] and others. An alternative is to express the dynamic equations in s ...

... with operation count of approximately the cube of the number of retained real modes and is not exact because of the linear approximations. Alternatively, Picard iteration can be used to solve the pseudo-uncoupled equations, see [11] and others. An alternative is to express the dynamic equations in s ...

Numerical Solution of Differential Equations with Orthogonal

... Furthermore if we differentiate Eq. (*) once, and evaluate it at all collocation points, we can write the first derivative in terms of the values at the collocation points. ...

... Furthermore if we differentiate Eq. (*) once, and evaluate it at all collocation points, we can write the first derivative in terms of the values at the collocation points. ...

Differential equations How to solve a general ODE numerically

... Making a flexible toolbox for solving ODEs We can continue to implement formulas for different numerical methods for ODEs – a new method just requires the formula, not the rest of the code needed to set initial conditions and loop in time The OO approach saves typing – no code duplication Challenge: ...

... Making a flexible toolbox for solving ODEs We can continue to implement formulas for different numerical methods for ODEs – a new method just requires the formula, not the rest of the code needed to set initial conditions and loop in time The OO approach saves typing – no code duplication Challenge: ...

Monte Carlo Simulations

... Although Type I error and power properties of statistics can be calculated for data drawn from classical theoretical distributions (e.g., normal curve, Cauchy distribution) for asymptotic conditions (i. e, infinite sample size and infinitesimally small treatment effect), real data often do not have ...

... Although Type I error and power properties of statistics can be calculated for data drawn from classical theoretical distributions (e.g., normal curve, Cauchy distribution) for asymptotic conditions (i. e, infinite sample size and infinitesimally small treatment effect), real data often do not have ...

Line search methods, Wolfe`s conditions

... 1.3. Convergence of line search methods. To obtain global convergence, we must not only have well chosen step lengths but also well-chosen directions pk . The angle θk between the search direction pk and the steepest descent direction −∇fk is defined by ∇fkT pk ...

... 1.3. Convergence of line search methods. To obtain global convergence, we must not only have well chosen step lengths but also well-chosen directions pk . The angle θk between the search direction pk and the steepest descent direction −∇fk is defined by ∇fkT pk ...

Monte Carlo Method www.AssignmentPoint.com Monte Carlo

... The modern version of the Markov Chain Monte Carlo method was invented in the late 1940s by Stanislaw Ulam, while he was working on nuclear weapons projects at the Los Alamos National Laboratory. Immediately after Ulam's breakthrough, John von Neumann understood its importance and programmed the ENI ...

... The modern version of the Markov Chain Monte Carlo method was invented in the late 1940s by Stanislaw Ulam, while he was working on nuclear weapons projects at the Los Alamos National Laboratory. Immediately after Ulam's breakthrough, John von Neumann understood its importance and programmed the ENI ...

a simple method of goal – directed lossy synthesis and network

... In the present time there are at disposal many analysis software products [4],[5] which can be used generally by a process of network optimization. These products can be used also directly to synthesis of goal – directed lossy structures without requirement of the special numerical algorithm impleme ...

... In the present time there are at disposal many analysis software products [4],[5] which can be used generally by a process of network optimization. These products can be used also directly to synthesis of goal – directed lossy structures without requirement of the special numerical algorithm impleme ...

¿Cuál debería ser el nivel de sencillez ideal para un análisis no

... The use of numerical tools consistent with the design procedures used for simpler analyses becomes thus encouraged for designers. A question arises then on how should a suitable nonlinear analysis be performed and how simple should it be. Two strategies are possible, the former consists on the use o ...

... The use of numerical tools consistent with the design procedures used for simpler analyses becomes thus encouraged for designers. A question arises then on how should a suitable nonlinear analysis be performed and how simple should it be. Two strategies are possible, the former consists on the use o ...

Meshing for Numerical Approach

... preprocessor stores geometrical (points, curves, surface, volumes, material) and numerical entities (nodes, edges, faces, elements). For example, ICEM stores them in “Parts”, ANSYS stores them in “Components”, Hypermesh stores them in “Collectors” and GAMBIT stores them in “Zones”. The sizing contro ...

... preprocessor stores geometrical (points, curves, surface, volumes, material) and numerical entities (nodes, edges, faces, elements). For example, ICEM stores them in “Parts”, ANSYS stores them in “Components”, Hypermesh stores them in “Collectors” and GAMBIT stores them in “Zones”. The sizing contro ...

Analysis and Numerics of the Chemical Master Equation

... of the CME via stochastic simulations is a simple and popular methodology [57, 4, 83, 84, 71]. This is because the two hardest aspects of solving via approximating the matrix exponential are trivial when solving via stochastic simulation. These two aspects are adaptivity and sub-division. Since the ...

... of the CME via stochastic simulations is a simple and popular methodology [57, 4, 83, 84, 71]. This is because the two hardest aspects of solving via approximating the matrix exponential are trivial when solving via stochastic simulation. These two aspects are adaptivity and sub-division. Since the ...

Chapter 6

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

Chapter 4 Methods

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

Numerical Methods for the solution of Hyperbolic

... to conservation laws, that is time-dependent systems of partial differential equations (PDEs), usually hyperbolic and nonlinear, with a particularly simple structure. Fluid and gas dynamics, relativity theory, quantum mechanics, aerodynamics, meteorology, astrophysics - this is just a partial list o ...

... to conservation laws, that is time-dependent systems of partial differential equations (PDEs), usually hyperbolic and nonlinear, with a particularly simple structure. Fluid and gas dynamics, relativity theory, quantum mechanics, aerodynamics, meteorology, astrophysics - this is just a partial list o ...

Introduction to Initial Value Problems

... Before we discuss methods for approximating the solution of the IVP (2.2) we first need to ask ourselves if our prototype IVP actually has an analytic solution, even if we are unable to find it. We are only interested in approximating the solution to IVPs which have a unique solution. However, even ...

... Before we discuss methods for approximating the solution of the IVP (2.2) we first need to ask ourselves if our prototype IVP actually has an analytic solution, even if we are unable to find it. We are only interested in approximating the solution to IVPs which have a unique solution. However, even ...

Section 5 slides - Emory Math/CS Department

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...

a new approach to solve fuzzy non-linear equations using fixed

... solution of the fuzzy non-linear equation is obtained with the help of the proposed algorithm and its graphical representation has also been shown as well. Some related definitions and some operations on linear fuzzy real numbers [3, 5-10], which will be used later to obtain a solution of fuzzy nonl ...

... solution of the fuzzy non-linear equation is obtained with the help of the proposed algorithm and its graphical representation has also been shown as well. Some related definitions and some operations on linear fuzzy real numbers [3, 5-10], which will be used later to obtain a solution of fuzzy nonl ...

R-97_ChenHB.pdf

... FEMs are not applicable, residue-based and recovery-based error estimation technology in FEM should be applied to meshless method selectively while characters of meshless methods should also be considered. (1) For the EFGM, investigations on error estimations are furnished more than other meshless ...

... FEMs are not applicable, residue-based and recovery-based error estimation technology in FEM should be applied to meshless method selectively while characters of meshless methods should also be considered. (1) For the EFGM, investigations on error estimations are furnished more than other meshless ...

Licentiate Thesis

... discretization error coming from the numerical methods; assuming ergodicity, statistical error coming from using a finite time; and modeling error coming from approximations related to the molecular dynamics. In Paper I, we address the modeling error. The aim is to determine quantitative error estim ...

... discretization error coming from the numerical methods; assuming ergodicity, statistical error coming from using a finite time; and modeling error coming from approximations related to the molecular dynamics. In Paper I, we address the modeling error. The aim is to determine quantitative error estim ...

Chebyshev Expansions - Society for Industrial and Applied

... For the case of a single interpolation node x0 which is repeated n times, the corresponding interpolating polynomial is just the Taylor polynomial of degree n at x0 . It is very common that successive derivatives of special functions are known at a certain point x = x0 (Taylor’s theorem, (2.1)), but ...

... For the case of a single interpolation node x0 which is repeated n times, the corresponding interpolating polynomial is just the Taylor polynomial of degree n at x0 . It is very common that successive derivatives of special functions are known at a certain point x = x0 (Taylor’s theorem, (2.1)), but ...

Adomian Method for Second-order Fuzzy Differential Equation

... HE study of fuzzy differential equation (FDE) forms a suitable setting for mathematical modeling of real world problems in which uncertainties or vagueness pervade. The concept of a fuzzy derivative was deﬁned by Chang and Zadeh in [13]. It was followed up by Dubois and Prade in [14], who used the e ...

... HE study of fuzzy differential equation (FDE) forms a suitable setting for mathematical modeling of real world problems in which uncertainties or vagueness pervade. The concept of a fuzzy derivative was deﬁned by Chang and Zadeh in [13]. It was followed up by Dubois and Prade in [14], who used the e ...