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Adaptive network used for estimation of sparse parameter vector

An adaptive network, sparse parameter technology, applied in network topology, digital transmission system, baseband system, etc., can solve the problems of slow convergence of sparse unknown parameter vector, low steady state imbalance, etc.

Active Publication Date: 2016-08-17
苏州容润通信技术有限公司
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Problems solved by technology

[0005] Purpose of the present invention: provide an adaptive network for sparse parameter vector estimation, which solves the problem of slow convergence of sparse unknown parameter vector estimation using DAPA's adaptive network, and can also have low steady-state imbalance at the same time

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  • Adaptive network used for estimation of sparse parameter vector
  • Adaptive network used for estimation of sparse parameter vector
  • Adaptive network used for estimation of sparse parameter vector

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[0043]In order to better illustrate the purpose and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following part will further illustrate the above scheme in combination with specific examples. It should be understood that these examples are used to illustrate the present invention and not to limit the scope of the present invention. The implementation conditions used in the examples can be adjusted according to specific applications, and the implementation conditions not indicated are generally the conditions in routine experiments.

[0044] Adopt the adaptive network of VSS-DPAPA method (abbreviated as VSS-DPAPA) in the present embodiment to identify an unknown parameter vector, and its performance and adopt DAPA method and adopt the adaptive network of DPAPA method (respectively abbreviated as DAPA Compared with the performance of DPAPA), the DPAPA metho...

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Abstract

The invention discloses an adaptive network used for estimation of a sparse parameter vector and belongs to the field of wireless sensor networks. Each node in the network comprises a wireless transceiver and an adaptive filter, wherein the wireless transceivers are used for receiving and sending data between nodes in neighborhoods, and the adaptive filters are used for estimating parameters through data received by the wireless transceivers; the adaptive filters included in the nodes in each neighborhood cooperate with a diffusion type variable-step-size proportion affine projection method to perform parameter estimation. Besides, for each network node, the time-variant step size of each adaptive filter is generated with noiseless priori error power and noise power, and higher convergence rate and lower steady-state maladjustment are obtained at the same time.

Description

technical field [0001] The invention discloses an adaptive network for estimation of sparse parameter vectors, in particular relates to parameter estimation using a proportional affine projection distribution method with variable step size, and belongs to the field of wireless sensor networks. Background technique [0002] An adaptive network is a communication network composed of multiple nodes scattered over an area, and data transmission is usually carried out between nodes in a specific way. Each node is equipped with an adaptive filter for adaptive estimation of unknown parameter vectors. At present, the application of adaptive network is very extensive, such as wireless sensor network, wireless spectrum estimation, target tracking and other fields. [0003] The main indicators to measure the performance of adaptive networks are convergence speed and steady-state misalignment. The convergence speed determines the time required for the adaptive network to estimate the ...

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Application Information

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IPC IPC(8): H04L25/02H04W84/18
CPCH04L25/0242H04W84/18
Inventor 倪锦根施娟
Owner 苏州容润通信技术有限公司
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