Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises
المؤلف
Hag ElAmin, Khalid Abd El Mageed
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-18
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
This study focused on the identification problems of two-input single-output system with moving average noises based on unsupervised learning methods applied to the input signals.
The input signal to the autoregressive moving average model is proposed to be arriving from a source with continuous technical and environmental changes as two separate featured input signals.
These two input signals were grouped in a number of clusters using the K-means clustering algorithm.
The clustered input signals were supplied to the model in an orderly fashion from cluster-1 up to cluster-K.
To ensure that the output signal can be best predicted from the input signal which in turn leads to selecting good enough model for its intended use, the magnitude-squared coherence (MSC) measure is applied to the input/output signals in the cases of clustered and nonclustered inputs, which indicates best correlation coefficient when measured with clustered inputs.
From collected input-output signals, we deduce a K-means clustering based recursive least squares method for estimating the parameter of autoregressive moving average system.
The simulation results indicate that the suggested method is effective.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hag ElAmin, Khalid Abd El Mageed. 2020. Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1141054
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hag ElAmin, Khalid Abd El Mageed. Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1141054
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hag ElAmin, Khalid Abd El Mageed. Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1141054
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1141054
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر