Search results for: multipath adaptive tabu search

Authors: R. Khorshidi , T. Niknam, M. Nayeripour

Abstract:

Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. Fueling the attention have been the possibilities of international agreements to reduce greenhouse gas emissions, electricity sector restructuring, high power reliability requirements for certain activities, and concern about easing transmission and distribution capacity bottlenecks and congestion. So it is necessary that impact of these kinds of generators on distribution feeder reconfiguration would be investigated. This paper presents an approach for distribution reconfiguration considering Distributed Generators (DGs). The objective function is summation of electrical power losses A Tabu search optimization is used to solve the optimal operation problem. The approach is tested on a real distribution feeder.

Keywords: Distributed Generator, Daily Optimal Operation, Genetic Algorithm.

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Authors: S. Anbu, N. Jaya

Abstract:

Nonlinearity is the inherent characteristics of all the industrial processes. The Classical control approach used for a generation often fails to show better results particularly for non-linear systems and in the systems, whose parameters changes over a period of time for a variety of reasons. Alternatively, adaptive control strategies provide very good performance. The Model Reference Adaptive Control based on Lyapunov stability analysis and classical PI control strategies are designed and evaluated for Continuous Stirred Tank Reactor, which shows appreciable dynamic nonlinear characteristics.

Keywords: Adaptive Control, CSTR, Lyapunov stability, MRAS, PID.

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Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing

Abstract:

The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.

Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.

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Authors: P. Acharjee, S. K. Goswami

Abstract:

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

Abstract:

Chaos and fractals are novel fields of physics and mathematics showing up a new way of universe viewpoint and creating many ideas to solve several present problems. In this paper, a novel algorithm based on the chaotic sequence generator with the highest ability to adapt and reach the global optima is proposed. The adaptive ability of proposal algorithm is flexible in 2 steps. The first one is a breadth-first search and the second one is a depth-first search. The proposal algorithm is examined by 2 functions, the Camel function and the Schaffer function. Furthermore, the proposal algorithm is applied to optimize training Multilayer Neural Networks.

Keywords: learning and evolutionary computing, Chaos Optimization Algorithm, Artificial Neural Networks, nonlinear optimization, intelligent computational technologies.

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Authors: Jan Erik Stellet

Abstract:

This article presents a detailed analysis and comparative performance evaluation of model reference adaptive control systems. In contrast to classical control theory, adaptive control methods allow to deal with time-variant processes. Inspired by the works [1] and [2], two methods based on the MIT rule and Lyapunov rule are applied to a linear first order system. The system is simulated and it is investigated how changes to the adaptation gain affect the system performance. Furthermore, variations in the reference model parameters, that is changing the desired closed-loop behaviour are examinded.

Keywords: Adaptive control systems, Adaptation gain, MIT rule, Lyapunov rule, Model reference adaptive control.

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Authors: Pankaj Swarnkar, Shailendra Jain, R.K Nema

Abstract:

Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. This paper deals with application of model reference adaptive control scheme in first order system. The rule which is used for this application is MIT rule. This paper also shows the effect of adaptation gain on the system performance. Simulation is done in MATLAB and results are discussed in detail.

Keywords: Adaptive control system, Adaptation gain, MIT rule, Model reference adaptive control.

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Authors: Hao Wu, Jonathan L. Shapiro

Abstract:

The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.

Keywords: Bayesian optimization algorithm, greedy search, KL divergence, stochastic search.

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Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi

Abstract:

In this paper, we propose an efficient hierarchical DNA sequence search method to improve the search speed while the accuracy is being kept constant. For a given query DNA sequence, firstly, a fast local search method using histogram features is used as a filtering mechanism before scanning the sequences in the database. An overlapping processing is newly added to improve the robustness of the algorithm. A large number of DNA sequences with low similarity will be excluded for latter searching. The Smith-Waterman algorithm is then applied to each remainder sequences. Experimental results using GenBank sequence data show the proposed method combining histogram information and Smith-Waterman algorithm is more efficient for DNA sequence search.

Keywords: Fast search, DNA sequence, Histogram feature, Smith-Waterman algorithm, Local search

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Authors: Neha Khanduja

Abstract:

This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID controller is tuned by using the concept of particle swarm optimization to get optimized operating point for minimum integral square error (ISE) condition. The results show the adjustment of PID parameters converting into the optimal operating point and the good control response can be obtained by the PSO technique.

Keywords: Model reference adaptive control (MRAC), optimal control, particle swarm optimization (PSO).

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Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong

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The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.

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Authors: Hyungkeun Jee, Jooyoung Lee, Dowon Hong

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The most common forensic activity is searching a hard disk for string of data. Nowadays, investigators and analysts are increasingly experiencing large, even terabyte sized data sets when conducting digital investigations. Therefore consecutive searching can take weeks to complete successfully. There are two primary search methods: index-based search and bitwise search. Index-based searching is very fast after the initial indexing but initial indexing takes a long time. In this paper, we discuss a high speed bitwise search model for large-scale digital forensic investigations. We used pattern matching board, which is generally used for network security, to search for string and complex regular expressions. Our results indicate that in many cases, the use of pattern matching board can substantially increase the performance of digital forensic search tools.

Keywords: Digital forensics, search, regular expression.

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Authors: Mario Kubek, Herwig Unger

Abstract:

Centroid terms are single words that semantically and topically characterise text documents and so may serve as their very compact representation in automatic text processing. In the present paper, centroids are used to measure the relevance of text documents with respect to a given search query. Thus, a new graphbased paradigm for searching texts in large corpora is proposed and evaluated against keyword-based methods. The first, promising experimental results demonstrate the usefulness of the centroid-based search procedure. It is shown that especially the routing of search queries in interactive and decentralised search systems can be greatly improved by applying this approach. A detailed discussion on further fields of its application completes this contribution.

Keywords: Search algorithm, centroid, query, keyword, cooccurrence, categorisation.

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Authors: R. Prabha, N. Ramaraj

Abstract:

Routing in adhoc networks is a challenge as nodes are mobile, and links are constantly created and broken. Present ondemand adhoc routing algorithms initiate route discovery after a path breaks, incurring significant cost to detect disconnection and establish a new route. Specifically, when a path is about to be broken, the source is warned of the likelihood of a disconnection. The source then initiates path discovery early, avoiding disconnection totally. A path is considered about to break when link availability decreases. This study modifies Adhoc On-demand Multipath Distance Vector routing (AOMDV) so that route handoff occurs through link availability estimation.

Keywords: Mobile Adhoc Network (MANET), Routing, Adhoc On-demand Multipath Distance Vector routing (AOMDV), Link Availability.

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Authors: M.Sujaritha, S. Annadurai

Abstract:

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.

Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.

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Authors: Hadi Adibi-Asl, Alireza Doosthosseini, Amir Taghavipour

Abstract:

This paper studies the design of an adaptive control strategy to tune an active steering system for better drivability and maneuverability. In the first step, adaptive control strategy is applied to estimate the uncertain parameters on-line (e.g. cornering stiffness), then the estimated parameters are fed into the pole placement controller to generate corrective feedback gain to improve the steering system dynamic’s characteristics. The simulations are evaluated for three types of road conditions (dry, wet, and icy), and the performance of the adaptive pole placement control (APPC) are compared with pole placement control (PPC) and a passive system. The results show that the APPC strategy significantly improves the yaw rate and side slip angle of a bicycle plant model.

Keywords: Adaptive control, active steering, pole placement, vehicle dynamics.

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Authors: Niklas Echterhoff, Benjamin Amshoff, Jürgen Gausemeier

Abstract:

Creativity is often based on an unorthodox recombination of knowledge; in fact: 80% of all innovations use given knowledge and put it into a new combination. Cross-industry innovations follow this way of thinking and bring together problems and solution ideas from different industries. Therefore analogies and search strategies have to be developed. Taking this path, the questions where to search, what to search and how to search have to be answered. Afterwards, the gathered information can be used within a planned search process. Identified solution ideas have to be assessed and analyzed in detail for the success promising adaption planning.

Keywords: analogy building, cross-industry innovations, knowledge transfer, solution adaption.

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Authors: Shahram Jafari, Mohammad-Ali Nikouei Mahani, Mohammad Arabnezhad, Mahdi Sharifi

Abstract:

Car accident is one of the major causes of death in many countries. Many researchers have attempted to design and develop techniques to increase car safety in the past recent years. In spite of all the efforts, it is still challenging to design a system adaptive to the driver rather than the automotive characteristics. In this paper, the adaptive car safety system is explained which attempts to find a balance.

Keywords: Analog to Digital Converter (ADC), AdaptiveCar Safety System, Multi-Media Card (MMC).

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Authors: Mario Kubek, Herwig Unger

Abstract:

Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.

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Authors: Young-Seok Choi

Abstract:

We present a family of data-reusing and affine projection algorithms. For identification of a noisy linear finite impulse response channel, a partial knowledge of a channel, especially noise, can be used to improve the performance of the adaptive filter. Motivated by this fact, the proposed scheme incorporates an estimate of a knowledge of noise. A constraint, called the adaptive noise constraint, estimates an unknown information of noise. By imposing this constraint on a cost function of data-reusing and affine projection algorithms, a cost function based on the adaptive noise constraint and Lagrange multiplier is defined. Minimizing the new cost function leads to the adaptive noise constrained (ANC) data-reusing and affine projection algorithms. Experimental results comparing the proposed schemes to standard data-reusing and affine projection algorithms clearly indicate their superior performance.

Keywords: Data-reusing, affine projection algorithm, error constraint, system identification.

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Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

Abstract:

This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: Adaptive filtering, multirate processing, normalized subband adaptive filter, source separation.

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Authors: Nikolaos Kroupis, Minas Dasygenis, Dimitrios Soudris, Antonios Thanailakis

Abstract:

One of the most growing areas in the embedded community is multimedia devices. Multimedia devices incorporate a number of complicated functions for their operation, like motion estimation. A multitude of different implementations have been proposed to reduce motion estimation complexity, such as spiral search. We have studied the implementations of spiral search and identified areas of improvement. We propose a modified spiral search algorithm, with lower computational complexity compared to the original spiral search. We have implemented our algorithm on an embedded ARM based architecture, with custom memory hierarchy. The resulting system yields energy consumption reduction up to 64% and performance increase up to 77%, with a small penalty of 2.3 dB, in average, of video quality compared with the original spiral search algorithm.

Keywords: Spiral Search, Motion Estimation, Embedded Systems, Low Power

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Authors: Abdel-Reza Hatamlou, Mohammad Reza Meybodi

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In this paper we present a hybrid search algorithm for solving constraint satisfaction and optimization problems. This algorithm combines ideas of two basic approaches: complete and incomplete algorithms which also known as systematic search and local search algorithms. Different characteristics of systematic search and local search methods are complementary. Therefore we have tried to get the advantages of both approaches in the presented algorithm. The major advantage of presented algorithm is finding partial sound solution for complicated problems which their complete solution could not be found in a reasonable time. This algorithm results are compared with other algorithms using the well known n-queens problem.

Keywords: Constraint Satisfaction Problem, Hybrid SearchAlgorithm.

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Authors: F. Sarabchi, M. E. Kalantari

Abstract:

In this paper, Optimum adaptive loading algorithms are applied to multicarrier system with Space-Time Block Coding (STBC) scheme associated with space-time processing based on singular-value decomposition (SVD) of the channel matrix over Rayleigh fading channels. SVD method has been employed in MIMO-OFDM system in order to overcome subchannel interference. Chaw-s and Compello-s algorithms have been implemented to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The adaptive loaded SVD-STBC scheme is capable of providing both full-rate and full-diversity for any number of transmit antennas. The effectiveness of these techniques has demonstrated through the simulation of an Adaptive loaded SVDSTBC system, and the comparison shown that the proposed algorithms ensure better performance in the case of MIMO.

Keywords: OFDM, MIMO, SVD, STBC, Adaptive Loading.

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Authors: Mert Turanli, Hakan Temeltas

Abstract:

In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: Adaptive control, Centroidal Voronoi Tessellations, composite adaptation, coordination.

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Authors: Esmail Limouzade, Mahmood.Joorabian, Najaf Hedayat

Abstract:

This paper undertakes the problem of optimal capacitor placement in a distribution system. The problem is how to optimally determine the locations to install capacitors, the types and sizes of capacitors to he installed and, during each load level,the control settings of these capacitors in order that a desired objective function is minimized while the load constraints,network constraints and operational constraints (e.g. voltage profile) at different load levels are satisfied. The problem is formulated as a combinatorial optimization problem with a nondifferentiable objective function. Four solution mythologies based on algorithms (GA),tabu search (TS), and hybrid GA-SA algorithms are presented.The solution methodologies are preceded by a sensitivity analysis to select the candidate capacitor installation locations.

Keywords: Genetic Algorithm (GA) , capacitor placement, voltage profile, network losses, Simulated Annealing, distribution network.

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Authors: Mohd Sazli Saad, Hishamuddin Jamaluddin, Intan Zaurah Mat Darus

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This paper presents the development of an active vibration control using direct adaptive controller to suppress the vibration of a flexible beam system. The controller is realized based on linear parametric form. Differential evolution optimisation algorithm is used to optimize the controller using single objective function by minimizing the mean square error of the observed vibration signal. Furthermore, an alternative approach is developed to systematically search for the best controller model structure together with it parameter values. The performance of the control scheme is presented and analysed in both time and frequency domain. Simulation results demonstrate that the proposed scheme is able to suppress the unwanted vibration effectively.

Keywords: flexible beam, finite difference method, active vibration control, differential evolution, direct adaptive controller

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Authors: Hikmat A. M. Abd-El-Jaber, Tengku M. T. Sembok

Abstract:

The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.

Keywords: information retrieval, user profiles, semantic Web, ontology, search engine.

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Authors: Young-Seok Choi

Abstract:

The Adaptive Line Enhancer (ALE) is widely used for enhancing narrowband signals corrupted by broadband noise. In this paper, we propose novel ALE methods to improve the enhancing capability. The proposed methods are motivated by the fact that the output of the ALE is a fine estimate of the desired narrowband signal with the broadband noise component suppressed. The proposed methods preprocess the input signal using ALE filter to regenerate a finer input signal. Thus the proposed ALE is driven by the input signal with higher signal-to-noise ratio (SNR). The analysis and simulation results are presented to demonstrate that the proposed ALE has better performance than conventional ALE’s.

Keywords: Adaptive filter, adaptive line enhancer, noise, feedback.

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Authors: Maged Ahmed, Ahmed El-Mahdy

Abstract:

In this paper, Selective Adaptive Parallel Interference Cancellation (SA-PIC) technique is presented for Multicarrier Direct Sequence Code Division Multiple Access (MC DS-CDMA) scheme. The motivation of using SA-PIC is that it gives high performance and at the same time, reduces the computational complexity required to perform interference cancellation. An upper bound expression of the bit error rate (BER) for the SA-PIC under Rayleigh fading channel condition is derived. Moreover, the implementation complexities for SA-PIC and Adaptive Parallel Interference Cancellation (APIC) are discussed and compared. The performance of SA-PIC is investigated analytically and validated via computer simulations.

Keywords: Adaptive interference cancellation, communicationsystems, multicarrier signal processing, spread spectrum

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