Treffer: Scientific programming with Java classes supported with a scripting interpreter

Title:
Scientific programming with Java classes supported with a scripting interpreter
Authors:
Source:
IET software (Print). 1(2):48-56
Publisher Information:
Stevenage: Institution of Engineering and Technology, 2007.
Publication Year:
2007
Physical Description:
print, 28 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Information Management, Technological Educational Institute of Kavala, Kavala 65404, Greece
ISSN:
1751-8806
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.18732305
Database:
PASCAL Archive

Weitere Informationen

jLab environment provides a Matlab/Scilab like scripting language that is executed by an interpreter, implemented in the Java language. This language supports all the basic programming constructs and an extensive set of built in mathematical routines that cover all the basic numerical analysis tasks. Moreover, the toolboxes of jLab can be easily implemented in Java and the corresponding classes can be dynamically integrated to the system. The efficiency of the Java compiled code can be directly utilised for any computationally intensive operations. Since jLab is coded in pure Java, the build from source process is much cleaner, faster, platform independent and less error prone than the similar C/C++/Fortran-based open source environments (e.g. Scilab and Octave). Neuro-Fuzzy algorithms can require enormous computation resources and at the same time an expressive programming environment. The potentiality of jLab is demonstrated by describing the implementation of a Support Vector Machine toolkit and by comparing its performance with a C/C++ and a Matlab version and across different computing platforms (i.e. Linux, Sun/Solaris and Windows XP).