adaptive-networks
所属分类：内容生成
开发工具：matlab
文件大小：20KB
下载次数：2
上传日期：2018-02-02 13:50:58
上 传 者：
sh-1993
说明： 扩散网络中模拟自适应和学习的代码
(Code to simulate Adaptation and Learning in Diffusion Networks)
文件列表:
LICENSE (1077, 2018-02-02)
example1.m (3812, 2018-02-02)
functions (0, 2018-02-02)
functions\adapt_nlms.m (1419, 2018-02-02)
functions\atc_nlms_acw.m (2719, 2018-02-02)
functions\atc_nlms_metropolis.m (2320, 2018-02-02)
functions\atc_nlms_nocoop.m (2259, 2018-02-02)
functions\datc_nlms_ls_exp.m (3526, 2018-02-02)
functions\filter_with_change.m (1334, 2018-02-02)
functions\get_algorithm_name_plot.m (244, 2018-02-02)
functions\get_dead_nodes.m (1632, 2018-02-02)
functions\sim_an.m (5067, 2018-02-02)
functions\static_combine_metropolis.m (1400, 2018-02-02)
functions\update_combine_acw.m (2023, 2018-02-02)
functions\update_combine_ls_exp.m (3289, 2018-02-02)
inputs (0, 2018-02-02)
inputs\example_basic.mat (1507, 2018-02-02)
inputs\example_complex.mat (1670, 2018-02-02)
# adaptive-networks
Code simulating Adaptation and Learning in Diffusion Networks
At this moment there are four implemented algorithms :
* ATC but with no cooperation
* ATC with Metropolis combination weights [1]
* ATC with Adaptive Combination Weights [2]
* Decoupled ATC for Estimation with LS adaptive Combiners [3]
## Example of use
See `example1.m` for an example of use
## References
[1] Cattivelli, F. S., & Sayed, A. H. (2010). Diffusion LMS strategies for distributed estimation. IEEE Transactions on Signal Processing, 58(3), 1035-1048.
[2] S-Y. Tu and A. H. Sayed, Optimal combination rules for adaptation and learning over networks, _Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing_ (CAMSAP), San Juan, Puerto Rico, pp. 317-320, December 2011.
[3 Fernandez-Bes, J., Arenas-Garca, J., Silva, M. T., & Azpicueta-Ruiz, L. A. (2017). Adaptive Diffusion Schemes for Heterogeneous Networks. IEEE Transactions on Signal Processing, 65(21), 5661-5674.
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