آمار
| تعداد نشریات | 31 |
| تعداد شماره‌ها | 734 |
| تعداد مقالات | 8,017 |
| تعداد مشاهده مقاله | 9,822,803 |
| تعداد دریافت فایل اصل مقاله | 9,301,933 |
دسته‌بندی کدگذارهای صوت در بستر شبکه‌های مخابراتی | ||
| مجله مهندسی برق دانشگاه تبریز | ||
| مقالات آماده انتشار، پذیرفته شده ، انتشار آنلاین از تاریخ 26 فروردین 1398 اصل مقاله (680.86 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| نویسندگان | ||
فرزانه جعفری؛ مهدی تیموری 
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| دانشکده علوم و فنون نوین - دانشگاه تهران | ||
| چکیده | ||
| داده‌های صوتی به‌طور گسترده‌ای در شبکه‌های مخابراتی در حال تبادل هستند. به‌دلیل محدودیت منابع شبکه، این داده‌ها معمولاً به‌صورت فشرده‌شده ارسال می‌شوند. روش‌های مختلفی برای فشرده‌سازی داده‌های صوت وجود دارد. لذا برای دسترسی غیرمجاز به اطلاعات صوتی، ابتدا باید نوع کدگذار به‌کاررفته در فشرده‌سازی صوت را شناسایی نمود. یکی از بهترین روش‌ها برای شناسایی نوع کدگذار داده‌های صوت، شناسایی بر اساس محتوای بسته‌های کدشده دریافتی است. در چنین روش‌هایی، نوع کدگذار به‌کاررفته برای تولید بسته‌های صوتی بر اساس ویژگی‌های آماری شناسایی می‌شود. در این مقاله، روشی برای دسته‌بندی کدگذارهای صوتی بر اساس دو ویژگی طولانی‌ترین زیررشته مشترک و طولانی‌ترین زیرتوالی مشترک پیشنهاد شده است. نتایج شبیه‌سازی نشان می‌دهد که عملکرد روش پیشنهادی (با صحت حدود %97 برای بسته‌های 8 کیلوبایتی) به‌شکل فراوانی بهتر از روش‌های موجود است. | ||
| کلیدواژه‌ها | ||
| کدگذارهای صوت؛ دسته‌بندی؛ طولانی‌ترین زیررشته مشترک؛ طولانی‌ترین زیرتوالی مشترک | ||
| عنوان مقاله [English] | ||
| Classification of Audio Codecs in Telecommunication Networks | ||
| نویسندگان [English] | ||
| F. Jafari؛ M. Teimouri | ||
| Faculty of New Science and Technology, University of Tehran, Tehran, Iran | ||
| چکیده [English] | ||
| Audio data are widely exchanged in telecommunications networks. Due to the limitation of network resources, these data are usually compressed before transmission. Various methods exist for compressing audio data. Hence, in order to unlawfully access these audio information, one needs to first identify the codec which is used for audio compression. One of the best approaches for audio codec identification is identification based on the contents of received packets. In these methods, statistical features of received packets are used for identification of employed codec. In this paper, a method of audio codec classification is proposed based on longest common substring and longest common subsequence features. Simulation results (with accuracy of 97% for 8 Kbytes packets) demonstrate the superiority of the proposed method compared to conventional methods. | ||
| کلیدواژه‌ها [English] | ||
| Audio codecs, classification, longest common substring, longest common subsequence | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 4 تعداد دریافت فایل اصل مقاله: 8 |
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