Search results for: adaptive filter
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1287

Search results for: adaptive filter

1077 A Fast Adaptive Tomlinson-Harashima Precoder for Indoor Wireless Communications

Authors: M. Naresh Kumar, Abhijit Mitra, C. Ardil

Abstract:

A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.

Keywords: Tomlinson-Harashima precoder, Adaptive channel estimation, Indoor wireless communication, Bit error rate.

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1076 Image Restoration in Non-Linear Filtering Domain using MDB approach

Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, C. Ardil

Abstract:

This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.

Keywords: Filtering, Minmax Detector Based (MDB), noise, centre weighted mean filter, PSNR, restoration.

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1075 Biological and Chemical Filter Treatment for Wastewater Reuse

Authors: M. J. Go, H. S. Shin, D. W. Kim, D. Chang, S. B. Han, J. M. Hur, B. R. Chung, J. K. Choi, J. Fan

Abstract:

This study developed a high efficient and combined biological and chemical filter treatment process. This process used PAC (Powder Activated Carbon), Alum and attached growth treatment process. The system removals of total nitrogen and total phosphorus ratio of two were as high as 70% and 73%, moreover, the effluent water was suitable to urban and agricultural water. Also the advantages of this process are not only occupies small place but is simple, economic and easy operating. Besides, our developed process can keep stable process efficiency even in relative low load level. Therefore, this study judges that use of the high efficient and combined biological and chemical filter treatment process, it is expected that the effluent water in this system can be reused as urban and agricultural water.

Keywords: biological and chemical filter treatment, wastewaterreuse, PAC, Alum

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1074 Crisis In/Out, Emergent, and Adaptive Urban Organisms

Authors: Y. Hadjichristou, A. Swiny, M. Georgiou

Abstract:

This paper focuses on the questions raised through the work of Unit 5: ‘In/Out Crisis, emergent and adaptive’; an architectural research-based studio at [ARC] University of Nicosia. Students were asked to delve into state of Art Technologies in order to propose sustainable Emergent and Adaptive Architectures and Urbanities, the resulting unprecedented spatial conditions and atmospheres of the emergent new ways of living are deemed to be the ultimate aim of the investigation. Students explored a variety of sites and crisis conditions seen through their primary ingredient identified as soil, water and air and their paired combination. Within this methodology, crisis is seen as a mechanism for allowing an emergence of new and fascinating ultimate sustainable future cultures and cities by taking advantage of the primary materiality of the sites.

Keywords: Adaptive built environments, crisis as opportunity, emergent urbanities, forces for inventions.

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1073 Adaptive Nonlinear Backstepping Control

Authors: Sun Lim, Bong-Seok Kim

Abstract:

This paper presents an adaptive nonlinear position controller with velocity constraint, capable of combining the input-output linearization technique and Lyapunov stability theory. Based on the Lyapunov stability theory, the adaptation law of the proposed controller is derived along with the verification of the overall system-s stability. Computer simulation results demonstrate that the proposed controller is robust and it can ensure transient stability of BLDCM, under the occurrence of a large sudden fault.

Keywords: BLDC Motor Control, Backstepping Control, Adaptive nonlinear control

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1072 Joint Adaptive Block Matching Search (JABMS) Algorithm

Authors: V.K.Ananthashayana, Pushpa.M.K

Abstract:

In this paper a new Joint Adaptive Block Matching Search (JABMS) algorithm is proposed to generate motion vector and search a best match macro block by classifying the motion vector movement based on prediction error. Diamond Search (DS) algorithm generates high estimation accuracy when motion vector is small and Adaptive Rood Pattern Search (ARPS) algorithm can handle large motion vector but is not very accurate. The proposed JABMS algorithm which is capable of considering both small and large motions gives improved estimation accuracy and the computational cost is reduced by 15.2 times compared with Exhaustive Search (ES) algorithm and is 1.3 times less compared with Diamond search algorithm.

Keywords: Adaptive rood pattern search, Block matching, Diamond search, Joint Adaptive search, Motion estimation.

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1071 Convergence Analysis of a Prediction based Adaptive Equalizer for IIR Channels

Authors: Miloje S. Radenkovic, Tamal Bose

Abstract:

This paper presents the convergence analysis of a prediction based blind equalizer for IIR channels. Predictor parameters are estimated by using the recursive least squares algorithm. It is shown that the prediction error converges almost surely (a.s.) toward a scalar multiple of the unknown input symbol sequence. It is also proved that the convergence rate of the parameter estimation error is of the same order as that in the iterated logarithm law.

Keywords: Adaptive blind equalizer, Recursive leastsquares, Adaptive Filtering, Convergence analysis.

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1070 A Tutorial on Dynamic Simulation of DC Motor and Implementation of Kalman Filter on a Floating Point DSP

Authors: Padmakumar S., Vivek Agarwal, Kallol Roy

Abstract:

With the advent of inexpensive 32 bit floating point digital signal processor-s availability in market, many computationally intensive algorithms such as Kalman filter becomes feasible to implement in real time. Dynamic simulation of a self excited DC motor using second order state variable model and implementation of Kalman Filter in a floating point DSP TMS320C6713 is presented in this paper with an objective to introduce and implement such an algorithm, for beginners. A fractional hp DC motor is simulated in both Matlab® and DSP and the results are included. A step by step approach for simulation of DC motor in Matlab® and “C" routines in CC Studio® is also given. CC studio® project file details and environmental setting requirements are addressed. This tutorial can be used with 6713 DSK, which is based on floating point DSP and CC Studio either in hardware mode or in simulation mode.

Keywords: DC motor, DSP, Dynamic simulation, Kalman Filter

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1069 Design and Synthesis of Two Tunable Bandpass Filters Based On Varactors and Defected Ground Structure

Authors: M. Boulakroune, M. Challal, H. Louazene, S. Fentiz

Abstract:

This paper presents two types of microstrip bandpass filter (BPF) at microwave frequencies. The first one is a tunable BPF using planar patch resonators based on a varactor diode. The filter is formed by a triple mode circular patch resonator with two pairs of slots, in which the varactor diodes are connected. Indeed, this filter is initially centered at 2.4 GHz; the center frequency of the tunable patch filter could be tuned up to 1.8 GHz simultaneously with the bandwidth, reaching high tuning ranges. Lossless simulations were compared to those considering the substrate dielectric, conductor losses and the equivalent electrical circuit model of the tuning element in order to assess their effects. Within these variations, simulation results showed insertion loss better than 2 dB and return loss better than 10 dB over the passband. The second structure is a BPF for ultra-wideband (UWB) applications based on multiple-mode resonator (MMR) and rectangular-shaped defected ground structure (DGS). This filter, which is compact size of 25.2 x 3.8 mm2, provides in the pass band an insertion loss of 0.57 dB and a return loss greater than 12 dB. The proposed filters presents good performances and the simulation results are in satisfactory agreement with the experimentation ones reported elsewhere.

Keywords: Defected ground structure, varactor diode, microstrip bandpass filter, multiple-mode resonator.

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1068 Adaptive Noise Reduction Algorithm for Speech Enhancement

Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

Abstract:

In this paper, Least Mean Square (LMS) adaptive noise reduction algorithm is proposed to enhance the speech signal from the noisy speech. In this, the speech signal is enhanced by varying the step size as the function of the input signal. Objective and subjective measures are made under various noises for the proposed and existing algorithms. From the experimental results, it is seen that the proposed LMS adaptive noise reduction algorithm reduces Mean square Error (MSE) and Log Spectral Distance (LSD) as compared to that of the earlier methods under various noise conditions with different input SNR levels. In addition, the proposed algorithm increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR improvement (ΔSNRseg) values; improves the Mean Opinion Score (MOS) as compared to that of the various existing LMS adaptive noise reduction algorithms. From these experimental results, it is observed that the proposed LMS adaptive noise reduction algorithm reduces the speech distortion and residual noise as compared to that of the existing methods.

Keywords: LMS, speech enhancement, speech quality, residual noise.

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1067 Static Single Point Positioning Using The Extended Kalman Filter

Authors: I. Sarras, G. Gerakios, A. Diamantis, A. I. Dounis, G. P. Syrcos

Abstract:

Global Positioning System (GPS) technology is widely used today in the areas of geodesy and topography as well as in aeronautics mainly for military purposes. Due to the military usage of GPS, full access and use of this technology is being denied to the civilian user who must then work with a less accurate version. In this paper we focus on the estimation of the receiver coordinates ( X, Y, Z ) and its clock bias ( δtr ) of a fixed point based on pseudorange measurements of a single GPS receiver. Utilizing the instantaneous coordinates of just 4 satellites and their clock offsets, by taking into account the atmospheric delays, we are able to derive a set of pseudorange equations. The estimation of the four unknowns ( X, Y, Z , δtr ) is achieved by introducing an extended Kalman filter that processes, off-line, all the data collected from the receiver. Higher performance of position accuracy is attained by appropriate tuning of the filter noise parameters and by including other forms of biases.

Keywords: Extended Kalman filter, GPS, Pseudorange

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1066 A Compact Via-less Ultra-Wideband Microstrip Filter by Utilizing Open-Circuit Quarter Wavelength Stubs

Authors: Muhammad Yasir Wadood, Fatemeh Babaeian

Abstract:

By developing ultra-wideband (UWB) systems, there is a high demand for UWB filters with low insertion loss, wide bandwidth, and having a planar structure which is compatible with other components of the UWB system. A microstrip interdigital filter is a great option for designing UWB filters. However, the presence of via holes in this structure creates difficulties in the fabrication procedure of the filter. Especially in the higher frequency band, any misalignment of the drilled via hole with the Microstrip stubs causes large errors in the measurement results compared to the desired results. Moreover, in this case (high-frequency designs), the line width of the stubs are very narrow, so highly precise small via holes are required to be implemented, which increases the cost of fabrication significantly. Also, in this case, there is a risk of having fabrication errors. To combat this issue, in this paper, a via-less UWB microstrip filter is proposed which is designed based on a modification of a conventional inter-digital bandpass filter. The novel approaches in this filter design are 1) replacement of each via hole with a quarter-wavelength open circuit stub to avoid the complexity of manufacturing, 2) using a bend structure to reduce the unwanted coupling effects and 3) minimising the size. Using the proposed structure, a UWB filter operating in the frequency band of 3.9-6.6 GHz (1-dB bandwidth) is designed and fabricated. The promising results of the simulation and measurement are presented in this paper. The selected substrate for these designs was Rogers RO4003 with a thickness of 20 mils. This is a common substrate in most of the industrial projects. The compact size of the proposed filter is highly beneficial for applications which require a very miniature size of hardware.

Keywords: Band-pass filters, inter-digital filter, microstrip, via-less.

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1065 An Efficient Digital Baseband ASIC for Wireless Biomedical Signals Monitoring

Authors: Kah-Hyong Chang, Xin Liu, Jia Hao Cheong, Saisundar Sankaranarayanan, Dexing Pang, Hongzhao Zheng

Abstract:

A digital baseband Application-Specific Integrated Circuit (ASIC) (yclic Redundancy Checkis developed for a microchip transponder to transmit signals and temperature levels from biomedical monitoring devices. The transmission protocol is adapted from the ISO/IEC 11784/85 standard. The module has a decimation filter that employs only a single adder-subtractor in its datapath. The filtered output is coded with cyclic redundancy check and transmitted through backscattering Load Shift Keying (LSK) modulation to a reader. Fabricated using the 0.18-μm CMOS technology, the module occupies 0.116 mm2 in chip area (digital baseband: 0.060 mm2, decimation filter: 0.056 mm2), and consumes a total of less than 0.9 μW of power (digital baseband: 0.75 μW, decimation filter: 0.14 μW).

Keywords: Biomedical sensor, decimation filter, Radio Frequency Integrated Circuit (RFIC) baseband, temperature sensor.

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1064 Deterministic Method to Assess Kalman Filter Passive Ranging Solution Reliability

Authors: Ronald M. Yannone

Abstract:

For decades, the defense business has been plagued by not having a reliable, deterministic method to know when the Kalman filter solution for passive ranging application is reliable for use by the fighter pilot. This has made it hard to accurately assess when the ranging solution can be used for situation awareness and weapons use. To date, we have used ad hoc rules-of-thumb to assess when we think the estimate of the Kalman filter standard deviation on range is reliable. A reliable algorithm has been developed at BAE Systems Electronics & Integrated Solutions that monitors the Kalman gain matrix elements – and a patent is pending. The “settling" of the gain matrix elements relates directly to when we can assess the time when the passive ranging solution is within the 10 percent-of-truth value. The focus of the paper is on surface-based passive ranging – but the method is applicable to airborne targets as well.

Keywords: Electronic warfare, extended Kalman filter (EKF), fighter aircraft, passive ranging, track convergence.

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1063 Comparative Study of Some Adaptive Fuzzy Algorithms for Manipulator Control

Authors: Sudeept Mohan, Surekha Bhanot

Abstract:

The problem of manipulator control is a highly complex problem of controlling a system which is multi-input, multioutput, non-linear and time variant. In this paper some adaptive fuzzy, and a new hybrid fuzzy control algorithm have been comparatively evaluated through simulations, for manipulator control. The adaptive fuzzy controllers consist of self-organizing, self-tuning, and coarse/fine adaptive fuzzy schemes. These controllers are tested for different trajectories and for varying manipulator parameters through simulations. Various performance indices like the RMS error, steady state error and maximum error are used for comparison. It is observed that the self-organizing fuzzy controller gives the best performance. The proposed hybrid fuzzy plus integral error controller also performs remarkably well, given its simple structure.

Keywords: Hybrid fuzzy, Self-organizing, Self-tuning, Trajectory tracking.

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1062 Adaptive Fourier Decomposition Based Signal Instantaneous Frequency Computation Approach

Authors: Liming Zhang

Abstract:

There have been different approaches to compute the analytic instantaneous frequency with a variety of background reasoning and applicability in practice, as well as restrictions. This paper presents an adaptive Fourier decomposition and (α-counting) based instantaneous frequency computation approach. The adaptive Fourier decomposition is a recently proposed new signal decomposition approach. The instantaneous frequency can be computed through the so called mono-components decomposed by it. Due to the fast energy convergency, the highest frequency of the signal will be discarded by the adaptive Fourier decomposition, which represents the noise of the signal in most of the situation. A new instantaneous frequency definition for a large class of so-called simple waves is also proposed in this paper. Simple wave contains a wide range of signals for which the concept instantaneous frequency has a perfect physical sense. The α-counting instantaneous frequency can be used to compute the highest frequency for a signal. Combination of these two approaches one can obtain the IFs of the whole signal. An experiment is demonstrated the computation procedure with promising results.

Keywords: Adaptive Fourier decomposition, Fourier series, signal processing, instantaneous frequency

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1061 Efficient Antenna Array Beamforming with Robustness against Random Steering Mismatch

Authors: Ju-Hong Lee, Ching-Wei Liao, Kun-Che Lee

Abstract:

This paper deals with the problem of using antenna sensors for adaptive beamforming in the presence of random steering mismatch. We present an efficient adaptive array beamformer with robustness to deal with the considered problem. The robustness of the proposed beamformer comes from the efficient designation of the steering vector. Using the received array data vector, we construct an appropriate correlation matrix associated with the received array data vector and a correlation matrix associated with signal sources. Then, the eigenvector associated with the largest eigenvalue of the constructed signal correlation matrix is designated as an appropriate estimate of the steering vector. Finally, the adaptive weight vector required for adaptive beamforming is obtained by using the estimated steering vector and the constructed correlation matrix of the array data vector. Simulation results confirm the effectiveness of the proposed method.

Keywords: Adaptive beamforming, antenna array, linearly constrained minimum variance, robustness, steering vector.

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1060 A Modified Speech Enhancement Using Adaptive Gain Equalizer with Non linear Spectral Subtraction for Robust Speech Recognition

Authors: C. Ganesh Babu, P. T. Vanathi

Abstract:

In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time Signal-to-Noise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of -5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGE-NSS) for robust speech recognition. The experimental result shows that out AGE-NSS performs the AGE when SNR drops below -5db level.

Keywords: Adaptive Gain Equalizer, Non Linear Spectral Subtraction, Speech Enhancement, and Speech Recognition.

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1059 Trajectory Control of a Robotic Manipulator Utilizing an Adaptive Fuzzy Sliding Mode

Authors: T. C. Kuo

Abstract:

In this paper, a novel adaptive fuzzy sliding mode control method is proposed for the robust tracking control of robotic manipulators. The proposed controller possesses the advantages of adaptive control, fuzzy control, and sliding mode control. First, system stability and robustness are guaranteed based on the sliding mode control. Further, fuzzy rules are developed incorporating with adaptation law to alleviate the input chattering effectively. Stability of the control system is proven by using the Lyapunov method. An application to a three-degree-of-freedom robotic manipulator is carried out. Accurate trajectory tracking as well as robustness is achieved. Input chattering is greatly eliminated.

Keywords: Fuzzy control, sliding mode control, roboticmanipulator, adaptive control.

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1058 Compact Dual-Band Bandpass Filter Based on Quarter Wavelength Stepped Impedance Resonators

Authors: Yu-Fu Chen, Zih-Jyun Dai, Chen-Te Chiu, Shiue-Chen Chiou, Yung-Wei Chen, Yu-Ming Lin, Kuan-Yu Chen, Hung-Wei Wu, Hsin-Ying Lee, Yan-Kuin Su, Shoou-Jinn Chang

Abstract:

This paper presents a compact dual-band bandpass filter that involves using the quarter wavelength stepped impedance resonators (SIRs) for achieving simultaneously compact circuit size and good dual-band performance. The filter is designed at 2.4 / 3.5 GHz and constructed by two pairs of quarter wavelength SIRs and source-load lines. By properly tuning the impedance ratio, length ratio and radius of via hole of the SIRs, dual-passbands performance can be easily determined. To improve the passband selectivity, the use of source-load lines is to increase coupling energy between the resonators. The filter is showing simple configuration, effective design method and small circuit size. The measured results are in good agreement with the simulation results.

Keywords: Dual-band, bandpass filter, stepped impedance resonators, SIR.

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1057 Variable Step-Size APA with Decorrelation of AR Input Process

Authors: Jae Wook Shin, Ju-man Song, Hyun-Taek Choi, Poo Gyeon Park

Abstract:

This paper introduces a new variable step-size APA with decorrelation of AR input process is based on the MSD analysis. To achieve a fast convergence rate and a small steady-state estimation error, he proposed algorithm uses variable step size that is determined by minimising the MSD. In addition, experimental results show that the proposed algorithm is achieved better performance than the other algorithms.

Keywords: adaptive filter, affine projection algorithm, variable step size.

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1056 Adaptive PID Control of Wind Energy Conversion Systems Using RASP1 Mother Wavelet Basis Function Networks

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

In this paper a PID control strategy using neural network adaptive RASP1 wavelet for WECS-s control is proposed. It is based on single layer feedforward neural networks with hidden nodes of adaptive RASP1 wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. This particular neuro PID controller assumes a certain model structure to approximately identify the system dynamics of the unknown plant (WECS-s) and generate the control signal. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.

Keywords: Adaptive PID Control, RASP1 Wavelets, WindEnergy Conversion Systems.

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1055 Speed Sensorless IFOC of PMSM Based On Adaptive Luenberger Observer

Authors: Grouz Faten, Sbita Lassaâd

Abstract:

In this paper, Speed Sensorless Indirect Field Oriented Control (IFOC) of a Permanent Magnet Synchronous machine (PMSM) is studied. The closed loop scheme of the drive system utilizes fuzzy speed and current controllers. Due to the well known drawbacks of the speed sensor, an algorithm is proposed in this paper to eliminate it. In fact, based on the model of the PMSM, the stator currents and rotor speed are estimated simultaneously using adaptive Luenberger observer for currents and MRAS (Model Reference Adaptive System) observer for rotor speed. To overcome the sensivity of this algorithm against parameter variation, adaptive for on line stator resistance tuning is proposed. The validity of the proposed method is verified by an extensive simulation work.

Keywords: PMSM, Indirect Field Oriented Control, fuzzy speed and currents controllers, Adaptive Luenberger observer, MRAS.

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1054 Adaptive MPC Using a Recursive Learning Technique

Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

Abstract:

A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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1053 Optimum Cascaded Design for Speech Enhancement Using Kalman Filter

Authors: T. Kishore Kumar

Abstract:

Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.

Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.

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1052 Variable Regularization Parameter Normalized Least Mean Square Adaptive Filter

Authors: Young-Seok Choi

Abstract:

We present a normalized LMS (NLMS) algorithm with robust regularization. Unlike conventional NLMS with the fixed regularization parameter, the proposed approach dynamically updates the regularization parameter. By exploiting a gradient descent direction, we derive a computationally efficient and robust update scheme for the regularization parameter. In simulation, we demonstrate the proposed algorithm outperforms conventional NLMS algorithms in terms of convergence rate and misadjustment error.

Keywords: Regularization, normalized LMS, system identification, robustness.

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1051 Novel Rao-Blackwellized Particle Filter for Mobile Robot SLAM Using Monocular Vision

Authors: Maohai Li, Bingrong Hong, Zesu Cai, Ronghua Luo

Abstract:

This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark position estimation and update is also implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem, and introducing the evolution strategies (ES) for avoiding particle impoverishment. The 3D natural point landmarks are structured with matching Scale Invariant Feature Transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-Tree in the time cost of O(log2 N). Experiment results on real robot in our indoor environment show the advantages of our methods over previous approaches.

Keywords: Mobile robot, simultaneous localization and mapping, Rao-Blackwellised particle filter, evolution strategies, scale invariant feature transform.

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1050 Speech Enhancement Using Kalman Filter in Communication

Authors: Eng. Alaa K. Satti Salih

Abstract:

Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.

Keywords: Autoregressive Process, Kalman filter, Matlab and Noise speech.

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1049 Downlink Scheduling and Radio Resource Allocation in Adaptive OFDMA Wireless Communication Systems for User-Individual QoS

Authors: Lu Yanhui, Wang Chunming, Yin Changchuan, Yue Guangxin

Abstract:

In this paper, we address the problem of adaptive radio resource allocation (RRA) and packet scheduling in the downlink of a cellular OFDMA system, and propose a downlink multi-carrier proportional fair (MPF) scheduler and its joint with adaptive RRA algorithm to distribute radio resources among multiple users according to their individual QoS requirements. The allocation and scheduling objective is to maximize the total throughput, while at the same time maintaining the fairness among users. The simulation results demonstrate that the methods presented provide for user more explicit fairness relative to RRA algorithm, but the joint scheme achieves the higher sum-rate capacity with flexible parameters setting compared with MPF scheduler.

Keywords: OFDMA, adaptive radio resource allocation, scheduling, QoS.

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1048 Performance Analysis of Adaptive OFDM Pre and Post-FTT Beamforming System

Authors: S. Elnobi, Iman El-Zahaby, Amr M. Mahros

Abstract:

In mobile communication systems, performance and capacity are affected by multi-path fading, delay spread and Co-Channel Interference (CCI). For this reason Orthogonal Frequency Division Multiplexing (OFDM) and adaptive antenna array are used is required. The goal of the OFDM is to improve the system performance against Inter-Symbol Interference (ISI). An array of adaptive antennas has been employed to suppress CCI by spatial technique. To suppress CCI in OFDM systems two main schemes the pre-FFT and the post-FFT have been proposed. In this paper, through a system level simulation, the behavior of the pre-FFT and post-FFT beamformers for OFDM system has been investigated based on two algorithms namely, Least Mean Squares (LMS) and Recursive Least Squares (RLS). The performance of the system is also discussed in multipath fading channel system specified by 3GPP Long Term Evolution (LTE).

Keywords: OFDM, Beamforming, Adaptive Antennas Array.

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