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Register a new userSound Data Compression Method Using Genetic Algorithm
طريقة لضغط بيانات الصوت باستخدام الخوارزمية الوراثية (الجينية)
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Damascus University ورقة بحثية
Publication date
2005
fields
Informatics Engineering
and research's language is
العربية
Authors
محمد عباس فاضل الحسيني( باحث )
Created by
Shamra Editor
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هدف هذا البحث هو تبني الخوارزمية الوراثية (الجينية) لدراستها أولاً، ثم التوقـف عنـد العمليات التي تقدم من قبل تلك الخوارزمية الوراثية. الحقـل المرشـح فـي هـذا البحـث لاستخدام وسائل الخوارزمية الوراثية و تطبيقاتها هو حقل ضغط بيانـات ملفـات الـصوت. يستخدم هذا البحث عمليات الخوارزمية الوراثية لتحسين عمل إحدى طرائق ضغط البيانـات الشائعة الاستخدام (VQ (Method Quantization Vector . بعد إجراء الدراسة علـى عمل الخوارزمية الوراثية، تم اقتراح خوارزمية لإجراء عملية المزج بـين طريقـة ضـغط البيانات ( VQ ) و مبدأ عمل الخوارزمية الوراثية. ثم اختبرت الخوارزمية المقترحـة مـن خلال كتابة البرامج الضرورية لذلك و تطبيقها على بعض بيانات ملفات الصوت، و قد أظهرت النتائج المسجلة إمكانية اعتماد خوارزمية المزج المقترحة لتحقيق أداء جيد لطريقة ( VQ ) في مجال ضغط بيانات ملفات الصوت.
The principal objective of this research is an adoption of the Genetic Algorithm (GA) for studying it firstly, and to stop over the operations which are introduced from the genetic algorithm.The candidate field for applying the operations of the genetic algorithm is the sound data compression field. This research uses the operations of the genetic algorithm for the enhancement of the performance of one of the popular compression method. Vector Quantization (VQ) method is selected in this work. After studying this method, new proposed algorithm for mixing the (GA) with this method was constructed and then the required programs for testing this algorithm was written. A good enhancement was recorded for the performance of the (VQ) method when mixed with the (GA). The proposed algorithm was tested by applying it on some sound data files. Some fidelity measures are calculated to evaluate the performance of the new proposed algorithm.
References used
Al-Rawi Hisham, Jane J. Stephan, “Genetic Algorithm Based Image Segmentation”, Proceeding of CATAEE’99, Philadelphia University, Jordan, 1999
Cabral Jim, “3D Vector Quantization of Magnetic Resonance Images”, Internet Paper, http://www.data-compression/vq.html, 1994
Chan Yuk-Hee, Wan-Chi Siu and Kin-Man Lam, “ A Novel VQ Encoding Algorithm Based on Adaptive Searching Sequence”, IEEE International Symposium on Speech, Image Processing and Neural Networks, 13-16 April 1994, Hong Kong
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