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A multitasking adaptive network for non-negative parameter vector estimation

An adaptive network and parameter vector technology, applied in network topology, wireless communication, electrical components, etc., to achieve the effect of fast convergence speed and low steady-state imbalance

Active Publication Date: 2021-01-26
SUZHOU UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0005] However, the existing multi-task diffusion LMS algorithm and multi-task diffusion RLS algorithm are only suitable for identifying unconstrained parameter vectors

Method used

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  • A multitasking adaptive network for non-negative parameter vector estimation
  • A multitasking adaptive network for non-negative parameter vector estimation
  • A multitasking adaptive network for non-negative parameter vector estimation

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[0028] 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.

[0029] Adopt the adaptive network of MD-NNLMAT method (abbreviated as MD-NNLMAT) in the present embodiment to identify an unknown parameter vector, and its performance and adopt the adaptive network of MD-NNLMS method (abbreviated as MD-NNLMS) The performance of the MD-NNLMS method is compared with the MD-NNLMAT method discl...

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Abstract

The invention discloses a multitasking adaptive network for non-negative parameter vector estimation, and belongs to the field of wireless sensor networks. The network is divided into a plurality of clusters, parameter vectors estimated by the clusters are the same, parameter vectors estimated by different clusters are different, but certain similarity exists between the parameter vectors. Meanwhile, due to constraints of some engineering applications, each node in the network needs to meet a non-negative constraint condition. The self-adaptive filter contained in each node adopts a multi-tasknonnegative cubic absolute value method to cooperatively carry out parameter estimation, so that a relatively high convergence rate is obtained.

Description

technical field [0001] The invention discloses a multi-task self-adaptive network for non-negative parameter vector estimation, in particular relates to a multi-task non-negative cubic absolute value method for parameter estimation, and belongs to the field of wireless sensor networks. Background technique [0002] The adaptive network is a communication network composed of multiple nodes scattered over an area, and each node is equipped with an adaptive filter, which is used to adaptively estimate the unknown parameter vector. At present, the application of multi-task adaptive network is very extensive. Each node in the network can use the interactive information of adjacent nodes to perform independent calculations, thereby improving the accuracy of the entire network identification. Multi-task adaptive networks have been widely used in applications such as machine learning and computer networks. [0003] According to the different cooperation modes of the nodes, the netw...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W24/02H04W84/18
CPCH04W24/02H04W84/18
Inventor 王紫璇
Owner SUZHOU UNIV
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