Search results for: Graph signal processing

Authors: Olesya Bolkhovskaya, Alexander Maltsev

Abstract:

Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference  spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signalis is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.

Keywords: GLRT, Neumann-Pearson’s criterion, test-statistics, degradation, spatial processing, multielement antenna array

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Authors: M.I.S. Ismail, Z. Taha

Abstract:

In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

Keywords: Plasma arc, hardened depth, surface roughness, Taguchi method, optimization.

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Authors: Nur Ilyani Ramli, Mansour Youseffi, Peter Widdop

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This paper presents a low cost design of heart beat monitoring device using reflectance mode PhotoPlethysmography (PPG). PPG is known for its simple construction, ease of use and cost effectiveness and can provide information about the changes in cardiac activity as well as aid in earlier non-invasive diagnostics. The proposed device is divided into three phases. First is the detection of pulses through the fingertip. The signal is then passed to the signal processing unit for the purpose of amplification, filtering and digitizing. Finally the heart rate is calculated and displayed on the computer using parallel port interface. The paper is concluded with prototyping of the device followed by verification procedure of the heartbeat signal obtained in laboratory setting.

Keywords: Reflectance mode PPG, Heart beat detection, Circuitdesign, PCB design

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Authors: Chien-Ju Li, Chun-Hui Yu, Chi-Chuan Hwang, Tsunglin Liu , Darby Tien-Hao Chang

Abstract:

De novo genome assembly is always fragmented. Assembly fragmentation is more serious using the popular next generation sequencing (NGS) data because NGS sequences are shorter than the traditional Sanger sequences. As the data throughput of NGS is high, the fragmentations in assemblies are usually not the result of missing data. On the contrary, the assembled sequences, called contigs, are often connected to more than one other contigs in a complicated manner, leading to the fragmentations. False connections in such complicated connections between contigs, named a contig graph, are inevitable because of repeats and sequencing/assembly errors. Simplifying a contig graph by removing false connections directly improves genome assembly. In this work, we have developed a tool, SIMGraph, to resolve ambiguous connections between contigs using NGS data. Applying SIMGraph to the assembly of a fungus and a fish genome, we resolved 27.6% and 60.3% ambiguous contig connections, respectively. These results can reduce the experimental efforts in resolving contig connections.

Keywords: Contig graph, NGS, de novo assembly, scaffold.

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Authors: Farooq Ahmad, Hejiao Huang, Xiaolong Wang

Abstract:

Reachability graph (RG) generation suffers from the problem of exponential space and time complexity. To alleviate the more critical problem of time complexity, this paper presents the new approach for RG generation for the Petri net (PN) models of parallel processes. Independent RGs for each parallel process in the PN structure are generated in parallel and cross-product of these RGs turns into the exhaustive state space from which the RG of given parallel system is determined. The complexity analysis of the presented algorithm illuminates significant decrease in the time complexity cost of RG generation. The proposed technique is applicable to parallel programs having multiple threads with the synchronization problem.

Keywords: Parallel processes, Petri net, reachability graph, time complexity.

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Authors: Matthias Dehmer, Frank Emmert Streib, Alexander Mehler, Jürgen Kilian, Max Mühlhauser

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Due to the tremendous amount of information provided by the World Wide Web (WWW) developing methods for mining the structure of web-based documents is of considerable interest. In this paper we present a similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as linear integer strings, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments for solving a novel and challenging problem: Measuring the structural similarity of generalized trees. In other words: We first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem for developing a efficient graph similarity measure. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based document structures.

Keywords: Graph similarity, hierarchical and directed graphs, hypertext, generalized trees, web structure mining.

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Authors: Tuhin Subhra Sarkar, Subir Das

Abstract:

Several research works have been done in recent times utilizing grayscale image for the measurement of many physical phenomena. In this present paper, we have designed an embedded based inclination sensor utilizing the grayscale image with a resolution of 0.3º. The sensor module consists of a circular shaped metal disc, laminated with grayscale image and an optical transreceiver. The sensor principle is based on temporal changes in light intensity by the movement of grayscale image with the inclination of the target surface and the variation of light intensity has been detected in terms of voltage by the signal processing circuit (SPC).The output of SPC is fed to a microcontroller program to display the inclination angel digitally. The experimental results are shown a satisfactory performance of the sensor in a small inclination measuring range of -40º to + 40º with a sensitivity of 62 mV/°.

Keywords: Grayscale image, Inclination Sensor, Microcontroller Program, Signal Processing Circuit.

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Authors: Toktam Zoughi, Reza Boostani

Abstract:

Determining depth of anesthesia is a challenging problem in the context of biomedical signal processing. Various methods have been suggested to determine a quantitative index as depth of anesthesia, but most of these methods suffer from high sensitivity during the surgery. A novel method based on energy scattering of samples in the wavelet domain is suggested to represent the basic content of electroencephalogram (EEG) signal. In this method, first EEG signal is decomposed into different sub-bands, then samples are squared and energy of samples sequence is constructed through each scale and time, which is normalized and finally entropy of the resulted sequences is suggested as a reliable index. Empirical Results showed that applying the proposed method to the EEG signals can classify the awake, moderate and deep anesthesia states similar to BIS.

Keywords: Depth of anesthesia, EEG, BIS, Wavelet transforms.

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Authors: Raida El Mansouri, Elhillali Kerkouche, Allaoua Chaoui

Abstract:

The Petri net tool INA is a well known tool by the Petri net community. However, it lacks a graphical environment to cerate and analyse INA models. Building a modelling tool for the design and analysis from scratch (for INA tool for example) is generally a prohibitive task. Meta-Modelling approach is useful to deal with such problems since it allows the modelling of the formalisms themselves. In this paper, we propose an approach based on the combined use of Meta-modelling and Graph Grammars to automatically generate a visual modelling tool for INA for analysis purposes. In our approach, the UML Class diagram formalism is used to define a meta-model of INA models. The meta-modelling tool ATOM3 is used to generate a visual modelling tool according to the proposed INA meta-model. We have also proposed a graph grammar to automatically generate INA description of the graphically specified Petri net models. This allows the user to avoid the errors when this description is done manually. Then the INA tool is used to perform the simulation and the analysis of the resulted INA description. Our environment is illustrated through an example.

Keywords: INA, Meta-modelling, Graph Grammars, AToM3, Automatic Code Generation.

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Authors: Parisa Shooshtari, Gelareh Mohamadi, Behnam Molaee Ardekani, Mohammad Bagher Shamsollahi

Abstract:

EEG signal is one of the oldest measures of brain activity that has been used vastly for clinical diagnoses and biomedical researches. However, EEG signals are highly contaminated with various artifacts, both from the subject and from equipment interferences. Among these various kinds of artifacts, ocular noise is the most important one. Since many applications such as BCI require online and real-time processing of EEG signal, it is ideal if the removal of artifacts is performed in an online fashion. Recently, some methods for online ocular artifact removing have been proposed. One of these methods is ARMAX modeling of EEG signal. This method assumes that the recorded EEG signal is a combination of EOG artifacts and the background EEG. Then the background EEG is estimated via estimation of ARMAX parameters. The other recently proposed method is based on adaptive filtering. This method uses EOG signal as the reference input and subtracts EOG artifacts from recorded EEG signals. In this paper we investigate the efficiency of each method for removing of EOG artifacts. A comparison is made between these two methods. Our undertaken conclusion from this comparison is that adaptive filtering method has better results compared with the results achieved by ARMAX modeling.

Keywords: Ocular Artifacts, EEG, Adaptive Filtering, ARMAX

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Authors: R. M. Farouk

Abstract:

In this paper, we present an analytical analysis of the representation of images as the magnitudes of their transform with the discrete wavelets. Such a representation plays as a model for complex cells in the early stage of visual processing and of high technical usefulness for image understanding, because it makes the representation insensitive to small local shifts. We found that if the signals are band limited and of zero mean, then reconstruction from the magnitudes is unique up to the sign for almost all signals. We also present an iterative reconstruction algorithm which yields very good reconstruction up to the sign minor numerical errors in the very low frequencies.

Keywords: Wavelets, Image processing signal processing, Image reconstruction

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Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, adaptive antenna array, Deep Neural Network, LS-SVM optimization model, radial basis function, MSE.

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Authors: Lin Cheng, Zijiang Yang

Abstract:

Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN.

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Authors: S.K.Ayyaswamy, S.Balachandran, K.Kannan

Abstract:

Let G be a graph of order n. The second stage adjacency matrix of G is the symmetric n × n matrix for which the ijth entry is 1 if the vertices vi and vj are of distance two; otherwise 0. The sum of the absolute values of this second stage adjacency matrix is called the second stage energy of G. In this paper we investigate a few properties and determine some upper bounds for the largest eigenvalue.

Keywords: Second stage spectral radius, Irreducible matrix, Derived graph

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Authors: Mahdi Taheri, Mehrana Niroumand

Abstract:

In this paper a new definition of adjacency matrix in the simple graphs is presented that is called fuzzy adjacency matrix, so that elements of it are in the form of 0 and n N n 1 , ∈ that are in the interval [0, 1], and then some charactristics of this matrix are presented with the related examples . This form matrix has complete of information of a graph.

Keywords: Graph, adjacency matrix, fuzzy numbers

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Authors: Gilberto Gonzalez-A, Gerardo Jaimes-A

Abstract:

A methodology to design a nonlinear observer in a bond graph approach is proposed. The class of nonlinear observer with multivariable nonlinearities is considered. A junction structure of the bond graph observer is proposed. The proposed methodology to an electrical transformer and a DC motor including the nonlinear saturation is applied. Nonlinear observers for the transformer and DC motor based on multivariable circle criterion in the physical domain are proposed. In order to show the saturation effects on the transformer and DC motor, simulation results are obtained. Finally, the paper describes that convergence of the estimates to the true states is achieved.

Keywords: Bond graph, nonlinear observer, electrical transformer, nonlinear saturation

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Authors: S. Balaji, V. Swaminathan, K. Kannan

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The Minimum Weighted Vertex Cover (MWVC) problem is a classic graph optimization NP - complete problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the minimum weighted vertex cover problem is to find a vertex set S V whose total weight is minimum subject to every edge of G has at least one end point in S. In this paper an effective algorithm, called Support Ratio Algorithm (SRA), is designed to find the minimum weighted vertex cover of a graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the SRA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Keywords: Weighted vertex cover, vertex support, approximation algorithms, NP-complete problem.

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Authors: Irene Luque Ruiz, Manuel Urbano Cuadrado, Miguel Ángel Gómez-Nieto

Abstract:

New graph similarity methods have been proposed in this work with the aim to refining the chemical information extracted from molecules matching. For this purpose, data fusion of the isomorphic and nonisomorphic subgraphs into a new similarity measure, the Approximate Similarity, was carried out by several approaches. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting several pharmacological parameters: binding of steroids to the globulin-corticosteroid receptor, the activity of benzodiazepine receptor compounds, and the blood brain barrier permeability. Acceptable results were obtained for the models presented here.

Keywords: Graph similarity, Nonisomorphic dissimilarity, Approximate similarity, Drug activity prediction.

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Authors: Ritu Vijay, Rekha Govil

Abstract:

The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: A. Mahfurdz, Sunardi, H. Ahmad

Abstract:

An envelope echo signal measurement is proposed in this paper using echo signal observation from the 200 kHz echo sounder receiver. The envelope signal without any object is compared with the envelope signal of the sphere. Two diameter size steel ball (3.1 cm & 2.2 cm) and two diameter size air filled stainless steel ball (4.8 cm & 7.4 cm) used in this experiment. The target was positioned about 0.5 m and 1.0 meter from the transducer face using nylon rope. From the echo observation in time domain, it is obviously shown that echo signal structure is different between the size, distance and type of metal sphere. The amplitude envelope voltage for the bigger sphere is higher compare to the small sphere and it confirm that the bigger sphere have higher target strength compare to the small sphere. Although the structure signal without any object are different compare to the signal from the sphere, the reflected signal from the tank floor increase linearly with the sphere size. We considered this event happened because of the object position approximately to the tank floor.

Keywords: echo sounder, target strength, sphere, echo signal

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Authors: Nazaket Gazieva

Abstract:

Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: Biometric voice prints, fundamental frequency, phonogram, speech signal, temporal characteristics.

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Authors: Sizhong Zhou, Bingyuan Pu

Abstract:

Let G be a graph of order n, and let a, b and m be positive integers with 1 ≤ a<b. An [a, b]-factor of G is defined as a spanning subgraph F of G such that a ≤ dF (x) ≤ b for each x ∈ V (G). In this paper, it is proved that if n ≥ (a+b−1+√(a+b+1)m−2)2−1 b and δ(G) > n + a + b − 2 √bn+ 1, then for any subgraph H of G with m edges, G has an [a, b]-factor F such that E(H)∩ E(F) = ∅. This result is an extension of thatof Egawa [2].

Keywords: graph, minimum degree, [a, b]-factor.

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

Abstract:

Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.

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Authors: Jehad Al Dallal

Abstract:

Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program backward slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. The existing algorithms for computing program slices are introduced to compute a slice at a program point. In these algorithms, the program, or the model that represents the program, is traversed completely or partially once. To compute more than one slice, the same algorithm is applied for every point of interest in the program. Thus, the same program, or program representation, is traversed several times. In this paper, an algorithm is introduced to compute all forward static slices of a computer program by traversing the program representation graph once. Therefore, the introduced algorithm is useful for software engineering applications that require computing program slices at different points of a program. The program representation graph used in this paper is called Program Dependence Graph (PDG).

Keywords: Program slicing, static slicing, forward slicing, program dependence graph (PDG).

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Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

Abstract:

A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: Noise signal, pulse interference, signal power, spectrum width, detection.

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Authors: Nuawi M. Z., Lamin F., Ismail A. R., Abdullah S., Wahid Z.

Abstract:

A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Keywords: Digital signal filtering, I-kaz method, Machiningmonitoring, Noise Cancelling, Sound

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Authors: Ahmad Salehi

Abstract:

An acyclic coloring of a graph G is a coloring of its vertices such that:(i) no two neighbors in G are assigned the same color and (ii) no bicolored cycle can exist in G. The acyclic chromatic number of G is the least number of colors necessary to acyclically color G. Recently it has been proved that any graph of maximum degree 5 has an acyclic chromatic number at most 8. In this paper we present another proof for this result.

Keywords: Acyclic Coloring, Vertex coloring.

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Authors: Vikas Rastogi, Vipan Kumar, Loveleen Kumar Bhagi

Abstract:

The present work deals with the structural analysis of turbine blades and modeling of turbine blades. A common failure mode for turbine machines is high cycle of fatigue of compressor and turbine blades due to high dynamic stresses caused by blade vibration and resonance within the operation range of the machinery. In this work, proper damping system will be analyzed to reduce the vibrating blade. The main focus of the work is the modeling of under platform damper to evaluate the dynamic analysis of turbine-blade vibrations. The system is analyzed using Bond graph technique. Bond graph is one of the most convenient ways to represent a system from the physical aspect in foreground. It has advantage of putting together multi-energy domains of a system in a single representation in a unified manner. The bond graph model of dry friction damper is simulated on SYMBOLS-shakti® software. In this work, the blades are modeled as Timoshenko beam. Blade Vibrations under different working conditions are being analyzed numerically.

Keywords: Turbine blade vibrations, Friction dampers, Timoshenko Beam, Bond graph modeling.

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Authors: Karima Siham Aoubid, Mohamed Boulemden

Abstract:

The development of the signal compression algorithms is having compressive progress. These algorithms are continuously improved by new tools and aim to reduce, an average, the number of bits necessary to the signal representation by means of minimizing the reconstruction error. The following article proposes the compression of Arabic speech signal by a hybrid method combining the wavelet transform and the linear prediction. The adopted approach rests, on one hand, on the original signal decomposition by ways of analysis filters, which is followed by the compression stage, and on the other hand, on the application of the order 5, as well as, the compression signal coefficients. The aim of this approach is the estimation of the predicted error, which will be coded and transmitted. The decoding operation is then used to reconstitute the original signal. Thus, the adequate choice of the bench of filters is useful to the transform in necessary to increase the compression rate and induce an impercevable distortion from an auditive point of view.

Keywords: Compression, linear prediction analysis, multiresolution analysis, speech signal.

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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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