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Performance of Gray Scaled Images Using Segmented Cellular Neural Network - Cellular Neural Network Combined Trellis Coded Quantization / Modulation (Scnn-Cnn Ctcq/Tcm) Approach Over Rician Fading Channel = Gri Tonlu Resimlerin Bölütlenmiş Hücresel Sinir Ağlarıyla Performans Analizi-Rician Kanal için Hücresel Sinir Ağı ile Birleştirilmiş Trellis Kodlu Kuantalama / Modülasyon (SCNN-CNN-CTCQ/TCM) Yaklaşımı

Author(s): Osman Nuri UÇAN | Atilla ÖZMEN

Journal: Dogus University Journal
ISSN 1302-6739

Issue: 1;
Start page: 217;
Date: 2000;
Original page

Keywords: Segmented cellular neural network | Trellis code quantization | Modulation | Rician fading channel

In this paper, Segmented Cellular Neural Network-Cellular Neural Network Combined Trellis Coded Quantization / Modulation (SCNN-CNN CTCQ/TCM) scheme is introduced. Here, a gray scaled image is lowered to 3 bit using our proposed Segmented Cellular Neural Network approach (SCNN) and then passed through a new CNN based structure which models combined trellis coded quantization / modulation. The performance of our combined scheme has been analyzed over Rician fading channel. Computer simulations studies confirm the analytical upper bound curves.
Affiliate Program     

Tango Jona
Tangokurs Rapperswil-Jona