کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10322135 | 660819 | 2014 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Artificial Neural Network trained by Particle Swarm Optimization for non-linear channel equalization
ترجمه فارسی عنوان
شبکه عصبی مصنوعی آموزش داده شده توسط بهینه سازی ذرات ذره برای مقیاس کانال غیر خطی
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کلمات کلیدی
شبکه های عصبی مصنوعی، بهینه سازی ذرات ذرات، مقیاس کانال،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In this paper, we apply Artificial Neural Network (ANN) trained with Particle Swarm Optimization (PSO) for the problem of channel equalization. Existing applications of PSO to Artificial Neural Networks (ANN) training have only been used to find optimal weights of the network. Novelty in this paper is that it also takes care of appropriate network topology and transfer functions of the neuron. The PSO algorithm optimizes all the variables, and hence network weights and network parameters. Hence, this paper makes use of PSO to optimize the number of layers, input and hidden neurons, the type of transfer functions etc. This paper focuses on optimizing the weights, transfer function, and topology of an ANN constructed for channel equalization. Extensive simulations presented in this paper shows that, as compared to other ANN based equalizers as well as Neuro-fuzzy equalizers, the proposed equalizer performs better in all noise conditions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 7, 1 June 2014, Pages 3491-3496
Journal: Expert Systems with Applications - Volume 41, Issue 7, 1 June 2014, Pages 3491-3496
نویسندگان
Gyanesh Das, Prasant Kumar Pattnaik, Sasmita Kumari Padhy,