In this work, a recently derived recursive least-square (RLS) algorithm to train multi layer perceptron (MLP) is used in an MLP-based decision feedback equalizer (DFE) instead of the back propagation (BP) algorithm. Its performance is investigated and compared to those of MLP-DFE based on the BP algorithm and the simple DFE based on the least-mean square (LMS) algorithm. The results show improv...

This paper presents the convergence analysis result of the discrete cosine transform-least-mean-square (DCT-LMS) adaptive "ltering algorithm which is based on a well-known interpretation of the variable stepsize algorithm. The time-varying stepsize of the DCT-LMS algorithm is implemented by the modi"ed power estimator to redistribute the spread power after the DCT. The performance analysis is c...

a r t i c l e i n f o a b s t r a c t Keywords: EEG/ERP Adaptive filter SNR LMS RLS ABC In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). ERP generated due to hand movement is filtered through...

Radio Frequency (RF) interference is inherent in all wireless systems and is one of the most significant design parameters of cellular and other mobile systems. In this paper, it is shown that how a non-linear adaptive Volterra filter (Polynomial filter where input and output signals are related through Volterra series) helps track the statistics of the input data and dynamics of a direct seque...

Wireless communication systems operating over time-varying fading channels require adaptive signal processing to equalize the channel variations at the receiver. In wireless applications, the received signal is typically affected by frequency-selective fading and channel equalization is required to mitigate the resulting inter symbol interference (ISI). In this paper an adaptive model has been ...

Intersymbol interference is an unwanted phenomenon that makes communication less reliable. However, an equalizer can reduce the bad influence of intersymbol interference. In general, my work is to compare different equalizers in various scenarios. In the first part of this paper, I explain the motivation of using equalization in detail, followed by introducing prerequisite knowledge of equaliza...

Channel State information can be determined by adaptive filtering algorithms for wireless channels. For slow fading channels, simplified channel estimators can be exploited such as Least Square Error (LSE) and Linear Minimum Mean Square Error (LMMSE). But for fast fading channels, the matrix inversion required in case of LMMSE has to be taken recursively which increase the complexity. Under suc...

This chapter provides an overview of interesting phenomena pertaining to the learning capabilities of stochastic-gradient adaptive filters, and in particular those of the least-mean-squares (LMS) algorithm. The phenomena indicate that the learning behavior of adaptive filters is more sophisticated, and also more favorable, than was previously thought, especially for larger step-sizes. The discu...

Frequency domain adaptive filtering has become increasingly popular due to its computational efficiency and excellent adaptation behavior. This paper proposes a new frequency domain based magnitude banded least mean-square(FDMBLMS) algorithm for the purpose of equalization of a rapidly time-variant channel. FDMBLMS implements a non-linear adaptation procedure based on the magnitude level of the...

There are various metaheuristic algorithms which are used to solve the Traveling Salesman problem. Ant colony optimization (ACO) is one such algorithm, which is inspired by the foraging behavior of ants. In this paper, we have proposed a modified model, entitled as Signed Adaptive Ant System (SAAS) for pheromone updation of the Ant-System; SAAS exploits the properties of Adaptive Filters. The p...