Signal-Comparison-Based Distributed Estimation under Decaying Average Data Rate Communications: Signal-comparison-based distributed estimation under decaying average data rate communications
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| Title: | Signal-Comparison-Based Distributed Estimation under Decaying Average Data Rate Communications: Signal-comparison-based distributed estimation under decaying average data rate communications |
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| Authors: | Jieming Ke, Xiaodong Lu, Yanlong Zhao, Ji-Feng Zhang |
| Source: | SIAM Journal on Control and Optimization. 63:1129-1155 |
| Publication Status: | Preprint |
| Publisher Information: | Society for Industrial & Applied Mathematics (SIAM), 2025. |
| Publication Year: | 2025 |
| Subject Terms: | Estimation and detection in stochastic control theory, Stochastic approximation, stochastic approximation, FOS: Electrical engineering, electronic engineering, information engineering, Distributed algorithms, Systems and Control (eess.SY), System identification, Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science), data rate, Electrical Engineering and Systems Science - Systems and Control, distributed estimation, event-triggered mechanism |
| Description: | The paper investigates the distributed estimation problem under low bit rate communications. Based on the signal-comparison (SC) consensus protocol under binary-valued communications, a new consensus+innovations type distributed estimation algorithm is proposed. Firstly, the high-dimensional estimates are compressed into binary-valued messages by using a periodic compressive strategy, dithered noises and a sign function. Next, based on the dithered noises and expanding triggering thresholds, a new stochastic event-triggered mechanism is proposed to reduce the communication frequency. Then, a modified SC consensus protocol is applied to fuse the neighborhood information. Finally, a stochastic approximation estimation algorithm is used to process innovations. The proposed SC-based algorithm has the advantages of high effectiveness and low communication cost. For the effectiveness, the estimates of the SC-based algorithm converge to the true value in the almost sure and mean square sense. A polynomial almost sure convergence rate is also obtained. For the communication cost, the local and global average bit rates for communications decay to zero at a polynomial rate. The trade-off between the convergence rate and the communication cost is established through event-triggered coefficients. A better convergence rate can be achieved by decreasing event-triggered coefficients, while lower communication cost can be achieved by increasing event-triggered coefficients. A simulation example is given to demonstrate the theoretical results. |
| Document Type: | Article |
| File Description: | application/xml |
| Language: | English |
| ISSN: | 1095-7138 0363-0129 |
| DOI: | 10.1137/24m1631328 |
| DOI: | 10.48550/arxiv.2405.18694 |
| Access URL: | http://arxiv.org/abs/2405.18694 https://zbmath.org/8029885 https://doi.org/10.1137/24m1631328 |
| Rights: | arXiv Non-Exclusive Distribution |
| Accession Number: | edsair.doi.dedup.....b424f9d44e64ad679320bfa1c6bd7f8c |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | The paper investigates the distributed estimation problem under low bit rate communications. Based on the signal-comparison (SC) consensus protocol under binary-valued communications, a new consensus+innovations type distributed estimation algorithm is proposed. Firstly, the high-dimensional estimates are compressed into binary-valued messages by using a periodic compressive strategy, dithered noises and a sign function. Next, based on the dithered noises and expanding triggering thresholds, a new stochastic event-triggered mechanism is proposed to reduce the communication frequency. Then, a modified SC consensus protocol is applied to fuse the neighborhood information. Finally, a stochastic approximation estimation algorithm is used to process innovations. The proposed SC-based algorithm has the advantages of high effectiveness and low communication cost. For the effectiveness, the estimates of the SC-based algorithm converge to the true value in the almost sure and mean square sense. A polynomial almost sure convergence rate is also obtained. For the communication cost, the local and global average bit rates for communications decay to zero at a polynomial rate. The trade-off between the convergence rate and the communication cost is established through event-triggered coefficients. A better convergence rate can be achieved by decreasing event-triggered coefficients, while lower communication cost can be achieved by increasing event-triggered coefficients. A simulation example is given to demonstrate the theoretical results. |
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| ISSN: | 10957138 03630129 |
| DOI: | 10.1137/24m1631328 |