Description: 利用最陡下降法仿真实现了自适应滤波均衡器,该方法用硬件能方便实现.-use of the steepest descent method Simulation of the adaptive filter equalizers, the method can be used to facilitate the achievement of hardware. Platform: |
Size: 2067 |
Author:研究生活 |
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Description: Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique. Platform: |
Size: 134537 |
Author:zhang |
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Description: This script runs a simulation loop for either a linear or a DFE equalizer. It
uses the RLS algorithm to initially set the weights, then uses LMS thereafter to minimize execution time. It plots the equalized signal spectrum, then generates and plots BER results over a range of Eb/No values. It also fits a curve to the simulated BER points, and plots the burst error performance of the linear and DFE equalizers. The adaptive equalizer objects automatically retain their state between invocations of their \"equalize\" method. Platform: |
Size: 2063 |
Author:熊牧野 |
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Description: 利用最陡下降法仿真实现了自适应滤波均衡器,该方法用硬件能方便实现.-use of the steepest descent method Simulation of the adaptive filter equalizers, the method can be used to facilitate the achievement of hardware. Platform: |
Size: 2048 |
Author:研究生活 |
Hits:
Description: Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique. -Adaptive Filter. This script shows the BER performance of several types of equalizers in a static channel with a null in the passband. The script constructs and implements a linear equalizer object and a decision feedback equalizer (DFE) object. It also initializes and invokes a maximum likelihood sequence estimation (MLSE) equalizer. The MLSE equalizer is first invoked with perfect channel knowledge, then with a straightforward but imperfect channel estimation technique. Platform: |
Size: 134144 |
Author:zhang |
Hits:
Description: This script runs a simulation loop for either a linear or a DFE equalizer. It
uses the RLS algorithm to initially set the weights, then uses LMS thereafter to minimize execution time. It plots the equalized signal spectrum, then generates and plots BER results over a range of Eb/No values. It also fits a curve to the simulated BER points, and plots the burst error performance of the linear and DFE equalizers. The adaptive equalizer objects automatically retain their state between invocations of their "equalize" method. Platform: |
Size: 2048 |
Author:熊牧野 |
Hits:
Description: 自适应均衡器设计用于抑制信号失真，自适应均衡器节拍系数是时变调整的。-Adaptive equalizers remove signal distortion attributed to intersymbol interference in band-limited
channels. The tap coefficients of adaptive equalizers are time-varying and can be adapted using
several methods. When these do not include the transmission of a training sequence, it is referred
to as blind equalization. Platform: |
Size: 14232576 |
Author:陈鹏 |
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Description: Adaptive equalization教程-Adaptive equalizers compensate for signal distortion
attributed to intersymbol interference (ISI), which is
caused by multipath within time-dispersive channels.
Typically employed in high-speed communication
systems, which do not use differential modulation
schemes or frequency division multiplexing
The equalizer is the most expensive component of a data
demodulator and can consume over 80 of the total
computations needed to demodulate a given signal [01]
Adaptive Equalization
KEVIN BANOVIC Slide 3
RESEARCH CENTRE FOR INTEGRATED MICROSYSTEMS – UNIVERSITY OF WINDSOR
EQUALIZATION TUTORIAL
Channel
Equalizer
Adjustment
FIR
Equalizer
Decision
Device
Error
Computation
s k ( ) y k ( )
e k ( )
r k ( ) s k ( )
Training
Sequence
Symbol
Statistics
Blind Mode
Decision-Directed
Mode Training Mode
Adaptive Equalization Platform: |
Size: 404480 |
Author:陈鹏 |
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Description: This paper compares performance of nite impulse
response (FIR) adaptive linear equalizers based on the recursive least-squares (RLS) and least mean square(LMS) algorithms in nonstationary uncorrelated scattering wireless channels. Simulation results, in terms of steady-state
mean-square estimation error (MSE) and average bit-error rate (BER) metrics, are found for the frequency selective Rayleigh fading wireless channel experienced in a mobile ad hoc network where nodes are lognormally shadowed from each other. For the nonstationary channel models considered, RLS is always found to outperform LMS. Platform: |
Size: 844800 |
Author:almoudamer3 |
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Description: Adaptive Blind Equalization Using Bottleneck Networks Implemented by Evolvable Hardware.Using a genetic
algorithm, the network on the hardware is trained to
minimize an energy function based on the maximum likelihood
estimation. Simulation results show that the proposed
equalizers have superior performance to popular CMA blind
equalizers. Platform: |
Size: 149504 |
Author:abd091 |
Hits:
Description: Adaptive equalizers remove signal distortion attributed to intersymbol interference in band-limited
channels. The tap coefficients of adaptive equalizers are time-varying and can be adapted using
several methods. When these do not include the transmission of a training sequence, it is referred
to as blind equalization. Platform: |
Size: 14232576 |
Author:Sinh |
Hits:
Description: These days, optical networks worldwide have been widely deployed in various network scales,
including long-haul backbone and metropolitan areas, as well as regional broadband access. In order
to assure a certain quality of service and a service-level agreement of the data delivery as requested
by the network service subscribers, network management plays a very important role in the operation
and administration of practical optical networks. Performance management is among the key aspects of
network management that assures the signal quality during signal transmission, switching, and routing.
It provides several important network functions including (1) providing feedback in the adaptive signal
compensators and equalizers (2) control of network elements (3) link setup, control, and optimization
and (4) fault forecasting, detection, diagnosis, and localization, as well as resilience mechanism
activation.-These days, optical networks worldwide have been widely deployed in various network scales,
including long-haul backbone and metropolitan areas, as well as regional broadband access. In order
to assure a certain quality of service and a service-level agreement of the data delivery as requested
by the network service subscribers, network management plays a very important role in the operation
and administration of practical optical networks. Performance management is among the key aspects of
network management that assures the signal quality during signal transmission, switching, and routing.
It provides several important network functions including (1) providing feedback in the adaptive signal
compensators and equalizers (2) control of network elements (3) link setup, control, and optimization
and (4) fault forecasting, detection, diagnosis, and localization, as well as resilience mechanism
activation. Platform: |
Size: 15537152 |
Author:mmessai |
Hits:
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