The development of reconfigurable and high throughput architectures is the utmost target for researchers in the field of Radio over Fiber (RoF). In this paper, we developed a cognitive radio over fiber system lined up...
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ISBN:
(纸本)9781509014682
The development of reconfigurable and high throughput architectures is the utmost target for researchers in the field of Radio over Fiber (RoF). In this paper, we developed a cognitive radio over fiber system lined up with Software Defined Networking owing to improve the quality of transport using a pre-equalization technique. The pre-equalization technique is based on Least Mean Square (lms) algorithm. It is used to compensate the optical link performance degradation in the RoF system. The simulation results of the overall Bit Error Rate (BER) and the Q factor attest of high system performance improvement.
In the realization of adaptive beamforming algorithms, the least-mean-squares (lms) algorithm had been the most popular scheme used for Smart Antenna systems. This Paper proposes an alternate scheme in the form of the...
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ISBN:
(纸本)9781424410934
In the realization of adaptive beamforming algorithms, the least-mean-squares (lms) algorithm had been the most popular scheme used for Smart Antenna systems. This Paper proposes an alternate scheme in the form of the Normalized lms (Nlms) algorithm with active tap detection for WCDMA systems. By taking advantage of spatial filtering, the proposed scheme promises to reduce the bandwidth required for transmitting data by improving convergence rate. The performance of the Frequency Domain Nlms algorithm in the presence of multipath effects and multiple users is analyzed using simulations. This analysis is compared to that of lms algorithm and suggests improvement in the convergence rate and number of active taps used, which leads to better system efficiency.
Performing distributed consensus in a network has been an important research problem for several years, and is directly applicable to sensor networks, autonomous vehicle formation, etc. While there exists a wide varie...
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ISBN:
(纸本)9781424442966
Performing distributed consensus in a network has been an important research problem for several years, and is directly applicable to sensor networks, autonomous vehicle formation, etc. While there exists a wide variety of algorithms that can be proven to asymptotically reach consensus, in applications involving time-varying parameters and tracking, it is often crucial to reach consensus "as quickly as possible". In [?] it has been shown that, with global knowledge of the network topology, it is possible to optimize the convergence time in distributed averaging algorithms via solving a semi-definite program (SDP) to obtain the optimal averaging weights. Unfortunately, in most applications, nodes do not have knowledge of the full network topology and cannot implement the required SDP in a distributed fashion. In this paper, we present a symmetric adaptive weight algorithm for distributed consensus averaging on bi-directional noiseless networks. The algorithm uses an lms (Least Mean Squares) approach to adaptively update the edge weights used to calculate each node's values. The derivation shows that global error can be minimized in a distributed fashion and that the resulting adaptive weights are symmetric-symmetry being critical for convergence to the true average. Simulations show that convergence time is nearly equal to that of a non-symmetric adaptive algorithm developed in [?], and significantly better than that of the non-adaptive Metropolis-Hastings algorithm. Most importantly, our symmetric adaptive algorithm converges to the sample mean, whereas the method of [?] converges to an arbitrary value and results in significant error.
Problem associated with biomedical signal like ECG is to extract noise cause by high frequency interference, electromagnetic fields, power line interference and body movement. It is difficult to apply filters with fix...
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ISBN:
(纸本)9781479917976
Problem associated with biomedical signal like ECG is to extract noise cause by high frequency interference, electromagnetic fields, power line interference and body movement. It is difficult to apply filters with fixed coefficients to reduce random noises. Adaptive filter technique is required to overcome this problem. This paper presents an innovative technique for estimation of ECG waves using Adaptive Noise Cancellation (ANC) algorithm, widrow-hoff lms algorithm. Comparisons are made for original signal to noisy. Simulations are done for random noise pattern in matlab.
The partial response maximum-likelihood (PRML) signal processing technique is effective for high-density recording media. However, asymmetry in the playback signal, which is caused not only by inter-symbol interferenc...
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The partial response maximum-likelihood (PRML) signal processing technique is effective for high-density recording media. However, asymmetry in the playback signal, which is caused not only by inter-symbol interference. but also by mismatched recording power in phase-change optical disks. markedly degrades the quality of PRML signal processing. In this paper, we propose an adaptive equalizer with a lms algorithm for asymmetrical signals. We show the improved results in recording and playback experiments.
This paper presents a new background calibration technique for pipelined ADCs by means of slow high accurate ADC (SHADC). Errors due to finite and nonlinear gain of inter-stage operational amplifier are calibrated. Co...
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ISBN:
(纸本)9781467356343
This paper presents a new background calibration technique for pipelined ADCs by means of slow high accurate ADC (SHADC). Errors due to finite and nonlinear gain of inter-stage operational amplifier are calibrated. Correction coefficients are estimated by using the well-known lms algorithm. Obtained results from simulation of a 13bit 1.5bit/stage pipelined ADC behavioral model reveals the effectiveness of the proposed technique to calibrate the mentioned errors. The ADC achieves a DNL of -0.8 LSB from -47.03 LSB, an INL of 2.84 LSB from 66.48 LSB and SNDR of 73.55 dB from 40.64 dB after calibration.
In this paper we study the problem of blind channel identification in chaotic communications. An adaptive algorithm is proposed, which exploits the boundness property of chaotic signals. Compared with the EKF-based ap...
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In this paper we study the problem of blind channel identification in chaotic communications. An adaptive algorithm is proposed, which exploits the boundness property of chaotic signals. Compared with the EKF-based approach, the proposed algorithm achieves a great complexity gain but at the expense of a slight accuracy degradation. However, our approach enjoys the important advantage that it does not require the a priori information such as nonlinearity of chaotic dynamics and the variances of measurement noise and the coefficient model noise. In addition, our approach is applicable to the ARMA system.
This paper introduces how to adopt adaptive lms algorithm to realize transverse delay filtering and IQ quadrature filtering. The performances of them are simulated in the case of strong interference. The simulation re...
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Ultrasonic sensing systems have been widely used for detection, recognition and measurement in industrial measurement, robotics, and so on. The narrow bandwidth feature of air medium ultrasonic transducer brings disad...
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ISBN:
(纸本)0780374886
Ultrasonic sensing systems have been widely used for detection, recognition and measurement in industrial measurement, robotics, and so on. The narrow bandwidth feature of air medium ultrasonic transducer brings disadvantages of bad ranging precision and distance resolution. In this paper a novel signal processing method is presented to overcome the limit caused by narrow bandwidth of ultrasonic transducer. We employed an equalizer based on transverse FIR filter employed to widen the bandwidth. The weights of this equalizer is trained with the lms adaptive algorithm. Experimental results show that the precision and target resolution of ultrasonic ranging system is improved.
Cílem práce bylo vyzkoušet metody potlačování 50 Hz brumu adaptivní filtrací. Při použití obecného adaptivního schématu a schématu pro potlačení deterministi...
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Cílem práce bylo vyzkoušet metody potlačování 50 Hz brumu adaptivní filtrací. Při použití obecného adaptivního schématu a schématu pro potlačení deterministického brumu. V práci je teoretické odvození adaptivního algoritmu a několik příkladů modelace v programu MATLAB.
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