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Design Of Optimal Linear Phase FIR High Pass Filter Using Craziness Based Particle Swarm Optimization Technique

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Mandal, Sangeeta (Author)
مؤلفين آخرين: Kar, Rajib (Co-Author) , Ghoshal, Sakti Prasad (Co-Author) , Mandal, Durbadal (Co-Author)
المجلد/العدد: مج24, ع1
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2012
الصفحات: 83 - 92
DOI: 10.33948/0584-024-001-009
ISSN: 1319-1578
رقم MD: 972058
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
كلمات المؤلف المفتاحية:
FIR Filter | PM Algorithm | RGA | PSO | Magnitude Response | High Pass (HP) Filter
رابط المحتوى:
صورة الغلاف QR قانون
حفظ في:
LEADER 02518nam a22002657a 4500
001 1715101
024 |3 10.33948/0584-024-001-009 
041 |a eng 
044 |b السعودية 
100 |9 523900  |a Mandal, Sangeeta  |e Author 
245 |a Design Of Optimal Linear Phase FIR High Pass Filter Using Craziness Based Particle Swarm Optimization Technique 
260 |b جامعة الملك سعود  |c 2012 
300 |a 83 - 92 
336 |a بحوث ومقالات  |b Article 
520 |b In this paper, an optimal design of linear phase digital high pass FIR filter using Craziness based Particle Swarm Optimization (CRPSO) approach has been presented. FIR filter design is a multi-modal optimization problem. The conventional gradient based optimization techniques are not efficient for such multi-modal optimization problem as they are susceptible to getting trapped on local optima. Given the desired filter specifications to be realized, the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the desired specifications. In birds' flocking or fish schooling, a bird or a fish often changes directions suddenly. This is described by using a "craziness" factor and is modeled in the CRPSO technique. In this paper, the realizations of the CRPSO based optimal FIR high pass filters of different orders have been performed. The simulation results have been compared to those obtained by the well accepted classical optimization algorithm such as Parks and McClellan algorithm (PM), and evolutionary algorithms like Real Coded Genetic Algorithm (RGA), and conventional Particle Swarm Optimization (PSO). The results justify that the proposed optimal filter design approach using CRPSO outperforms PM, RGA and PSO, in the optimal characteristics of frequency spectrums. 
653 |a برامج الحاسوب  |a الوسائط المتعددة  |a الخوارزميات 
692 |b FIR Filter  |b PM Algorithm  |b RGA  |b PSO  |b Magnitude Response  |b High Pass (HP) Filter 
700 |9 523902  |a Kar, Rajib  |e Co-Author 
700 |9 523901  |a Ghoshal, Sakti Prasad  |e Co-Author 
773 |c 009  |e Journal of King Saud University (Computer and Information Sciences)  |f Maǧalaẗ ǧamʼaẗ al-malīk Saud : ùlm al-ḥasib wa al-maʼlumat  |l 001  |m مج24, ع1  |o 0584  |s مجلة جامعة الملك سعود - علوم الحاسب والمعلومات  |v 024  |x 1319-1578 
700 |9 523903  |a Mandal, Durbadal  |e Co-Author 
856 |u 0584-024-001-009.pdf 
930 |d y  |p y 
995 |a science 
999 |c 972058  |d 972058