On Modified Complex Recurrent Neural Network Adaptive Equalizer
نویسندگان
چکیده
A new modified version called decision feedback complex recurrent neural network equalizer (DFCRNNE) is proposed with the study of complex recurrent neural network equalizer (CRNNE). Based on DFCRNNE, a modified real time recurrent learning (CRTRL) algorithm is developed. Simulation results show that DFCRNNE has better performance than CRNNE based on traditional CRTRL algorithm2 in complex nonlinear channels with severe intersymbol interference (ISI) and nonlinear distortion.
منابع مشابه
Image Backlight Compensation Using Recurrent Functional Neural Fuzzy Networks Based on Modified Differential Evolution
In this study, an image backlight compensation method using adaptive luminance modification is proposed for efficiently obtaining clear images.The proposed method combines the fuzzy C-means clustering method, a recurrent functional neural fuzzy network (RFNFN), and a modified differential evolution.The proposed RFNFN is based on the two backlight factors that can accurately detect the compensat...
متن کاملAdaptive Channel Equalizer using Combination of FIR and Functional Link Artificial Neural Network for Complex Signals
− This paper proposes an adaptive nonlinear channel equalizer by using combination of finite impulse response (FIR) filter and functional link artificial neural (FLANN) network (CFFLANN) capable of equalizing complex multilevel signals. The equalizer is designed to remove linear and nonlinear distortion produced by nonlinear channel. FLANN section removes the nonlinear distortions and FIR secti...
متن کاملUsing Neural Networks for Adaptive Equalization
. Non linrea distortion introduced by communications channels increases the probability of error. Application of artificial neural network structures to the problem of channel equalizationin a digital communication system has been considered in this paper. The difficulties associated with channel non linearities can be overcome by equalizers employing diagonal recurrent neural network (DRNN). B...
متن کاملRecurrent Canonical Piecewise Linear Network and Its Application to Adaptive Equalization - Neural Networks, 1996., IEEE International Conference on
In this paper, we present a recurrent canonical piecewise linear (RCPL) network based on canonical piecewise-linear (CPL) function and autoregressive moving average model, and apply it to adaptive channel equalization. It, is shown that a recurrent neural network with piecewise linear activation function realizes an RCPL network. RCPL network has several advantages: First, i t can make use of s...
متن کاملComplex bilinear recurrent neural network for equalization of a digital satellite channel
Equalization of satellite communication using complex-bilinear recurrent neural network (C-BLRNN) is proposed. Since the BLRNN is based on the bilinear polynomial, it can be used in modeling highly nonlinear systems with time-series characteristics more effectively than multilayer perceptron type neural networks (MLPNN). The BLRNN is first expanded to its complex value version (C-BLRNN) for dea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Journal of Circuits, Systems, and Computers
دوره 11 شماره
صفحات -
تاریخ انتشار 2002