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Distributed sparse diffusion estimation with reduced communication cost

IET SIGNAL PROCESSING 2018年第8期12卷 1043-1052页

作者： Shiri, Hamid Tinati, Mohammad Ali Codreanu, Marian Azarnia, Ghanbar Univ Tabriz Dept Elect & Comp Engn Tabriz 51666 Iran Univ Oulu Ctr Wireless Commun Oulu 90014 Finland

The issue considered in the current study is the problem of adaptive distributed estimation based on diffusion strategy which can exploit sparsity in improving estimation error and reducing communications. It has been shown that distributed estimation leads to a good performance in terms of the error value, convergence rate, and robustness against node and link failures in wireless sensor networks. However, the main focus of many works in the field of distributed estimation research is on convergence speed and estimation error, neglecting the fact that communications among the nodes require a lot of transmissions. In this work, the focus is on a solution based on sparse diffusion least mean squares (LMS) algorithm, and a new version of sparse diffusion LMS algorithm is proposed which takes both communications and error cost into account. Also, the computation complexity and communication cost for every node of the network, as well as performance analysis of the proposed strategy, is provided. The performance of the proposed method in comparison with the existing methods is illustrated by means of simulations in terms of computational and communicational cost, and flexibility to signal changes.

关键词： computational complexity adaptive estimation wireless sensor networks least mean squares methods network theory (graphs) convergence rate wireless sensor networks distributed estimation research convergence speed estimation error sparse diffusion least mean squares algorithm sparse diffusion LMS algorithm computation complexity computational cost communicational cost distributed sparse diffusion estimation reduced communication cost adaptive distributed estimation diffusion strategy

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EAdderSR: enhanced AdderSR for single image super resolution

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APPLIED INTELLIGENCE 2023年第18期53卷 20998-21011页

作者： Song, Jie Yi, Huawei Xu, Wenqian Li, Xiaohui Li, Bo Liu, Yuanyuan Liaoning Univ Technol Sch Elect & Informat Engn Jinzhou 121001 Peoples R China Dalian Univ Key Lab Adv Design & Intelligent Comp Minist Educ Dalian 116622 Peoples R China

Replacing multiplication with addition can effectively reduce the computational complexity. Based on this idea, adder neural networks (AdderNets) are proposed. Thereafter, AdderNets are applied to super-resolution (SR) task to obtain AdderSR, which significantly reduces the energy consumption caused by SR models. However, the weak fitting ability of AdderNets makes AdderSR only applicable to the low-complexity pixel-wise loss, and the performance of the model drops sharply when the high-complexity perceptual loss is used. Enhanced AdderSR (EAdderSR) is proposed to overcome the limitations of AdderSR in SR tasks. Specifically, current adder networks have serious gradient precision loss problem, which affects the training stability. The normalization layer is adjusted to normalize the output of the adder layer to a reasonably narrow range, which can reduce the amount of precision loss. Then, a coarse-grained knowledge distillation (CGKD) method is developed to give adder networks an efficient guidance to reduce the fitting burden. The experimental results show that the proposed method not only further improves the performance of adder networks, but also ensures the quality of the output results when the complexity of the loss function increases.

关键词： Super resolution Adder neural network computation complexity Knowledge distillation

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Approximating the Partition Function of the Ferromagnetic Potts Model

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JOURNAL OF THE ACM 2012年第5期59卷 1–31页

作者： Goldberg, Leslie Ann Jerrum, Mark Univ Liverpool Dept Comp Sci Liverpool L69 3BX Merseyside England Univ London Sch Math Sci London E1 4NS England

We provide evidence that it is computationally difficult to approximate the partition function of the ferromagnetic q-state Potts model when q > 2. Specifically, we show that the partition function is hard for the complexity class #RH Pi(1) under approximation-preserving reducibility. Thus, it is as hard to approximate the partition function as it is to find approximate solutions to a wide range of counting problems, including that of determining the number of independent sets in a bipartite graph. Our proof exploits the first-order phase transition of the "random cluster" model, which is a probability distribution on graphs that is closely related to the q-state Potts model.

关键词： Theory Approximation algorithms computation complexity phase transition Potts model random cluster model statistical physics Tutte polynomial

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Two secret sharing schemes based on Boolean operations

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PATTERN RECOGNITION 2007年第10期40卷 2776-2785页

作者： Wang, Daoshun Zhang, Lei Ma, Ning Li, Xiaobo Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Univ Alberta Dept Comp Sci Edmonton AB Canada

Traditional secret sharing schemes involve complex computation. A visual secret sharing (VSS) scheme decodes the secret without computation, but each shadow is m times as big as the original. Probabilistic VSS solved the computation complexity and space complexity problems at once. In this paper we propose a probabilistic (2, n) scheme for binary images and a deterministic (n, n) scheme for grayscale images. Both use simple Boolean operations and both have no pixel expansion. The (2, n) scheme provides a better contrast and significantly smaller recognized areas than other methods. The (n, n) scheme gives an exact reconstruction. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： secret sharing scheme visual secret sharing visual cryptography computation complexity pixel expansion

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Enhancing the performance of transmission line directional relaying, fault classification and fault location schemes using fuzzy inference system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第6期9卷 580-591页

作者： Yadav, Anamika Swetapadma, Aleena Natl Inst Technol Dept Elect Engn Raipur CG India

This study aims to improve the performance of transmission line directional relaying, fault classification and fault location schemes using fuzzy system. Three separate fuzzy inference system are designed for complete protection scheme for transmission line. The proposed technique is able to accurately detect the fault (both forward and reverse), locate and also identify the faulty phase(s) involved in all ten types of shunt faults that may occur in a transmission line under different fault inception angle, fault resistances and fault location. The proposed method needs current and voltage measurements available at the relay location and can perform the fault detection and classification in about a half-cycle time. The proposed fuzzy logic based relay has less computation complexity and is better than other AI based methods such as artificial neural network, support vector machine, and decision tree (DT) etc. which require training. The percentage error in fault location is within 1 km for most of the cases. Fault location scheme has been validated using. 2 test with 5% level of significance. Proposed scheme is a setting free method and is suitable for wide range of parameters, fault detection time is less than half cycle and relay does not show any reaching mal-operation so it is reliable, accurate and secure.

关键词： support vector machine shunt faults relay protection Power transmission, distribution and supply fault diagnosis fault resistances Power system protection fault classification transmission line protection scheme fault location schemes Knowledge engineering techniques artificial neural network current measurements voltage measurements Formal logic fuzzy inference system transmission line directional relaying performance enhancement computation complexity fault detection fuzzy logic based relay half-cycle time power transmission protection fuzzy logic fault inception angle AI based methods relay location fuzzy reasoning power engineering computing computational complexity power transmission lines Power engineering computing

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computational Scheme of Ordinary Differential Equations Integration on the Basis of Differential Taylor Transformation with Automatic Step and Order Selection

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JOURNAL OF AUTOMATION AND INFORMATION SCIENCES 2012年第12期44卷 12-22页

作者： Rakushev, M. Yu. Natl Aviat Univ Zhitomir SP Korolev Mil Inst Kiev Ukraine

The computational scheme of ordinary differential equations integration with the automatic step size and order selection of the scheme developed on the basis of differential Taylor transformation is offered. The adapt ation at each step of integration is conducted based on providing the desired precision at the minimum computational efforts. The results of simulation are presented.

关键词： ordinary differential equations differential Taylor transformation computation complexity automatic step size and order selection

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computationally efficient and secure anonymous authentication scheme for cloud users

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PERSONAL AND UBIQUITOUS COMPUTING 2021年第1期28卷 111-121页

作者： Arasan, Anakath Sadaiyandi, Rajakumar Al-Turjman, Fadi Rajasekaran, Arun Sekar Karuppuswamy, Kalai Selvi EGS Pillay Engn Coll Sch Comp Nagapattinam TN India Univ Coll Engn Ariyalur Dept Math Ariyalur TN India Near East Univ Res Ctr AI & IoT Artificial Intelligence Engn Dept 10 Mersin Nicosia Turkey GMR Inst Technol Dept ECE Rajam Andhra Pradesh India SNS Coll Technol Coimbatore 35 Tamil Nadu India

In cloud computing, the combinations of various computing units are globally separated, however, electronically connected. In recent years, the number of cloud users has adequately increased in the modern societies. In order to restrict the illegal access of the intruders, a strong user authentication is required for cloud computing environment. In this regard, in this paper, we came up with a computationally productive and safer anonymous authentication pattern for cloud users. Moreover, in our scheme, mutual authentication is performed in an anonymous way between the cloud user and the cloud server to strongly verify the legitimacy of each user before providing an access into the cloud. After the successful anonymous mutual authentication, the targeted cloud service provider and the cloud users make mutual communication between them. In case of any misbehaviouring after successful mutual authentication, an efficient revocation mechanism is proposed through which the trusted third party (TTP) can revoke the cloud users or service providers from the cloud environment. Even though there were many anonymous cloud computing authentication schemes, the previously proposed authentication schemes suffered from high computational cost during certificate verification. Moreover, the section related to analysis proves that the explained scheme is robust enough in terms of security strength to avoid various security attacks and breeches.

关键词： Authentication computation complexity Privacy Conditional tracking Data integrity

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Joint frequency and two-dimensional direction of arrival estimation for Electronic Support systems based on sub-Nyquist sampling

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IET RADAR SONAR AND NAVIGATION 2018年第8期12卷 889-899页

作者： Ramezani, Esmaeil Sabahi, Mohamad Farzan Saberali, Seyyed Mohammad Univ Isfahan Dept Elect Engn Esfahan Iran

The electronic support (ES) receivers require wide instantaneous bandwidth as a result of a wide-frequency range of modern radar signals. Thus, analogue-to-digital converters (ADCs) with high sampling rates are required for digital ES receivers. One of the bottlenecks in designing such systems is the high power consumption of the back-end ADCs at high sampling rates. In this study, a system-level approach with the goal of minimising the required digitisation rate is presented by exploiting compressive sampling. Using the proposed receiver structure, the location finding of pulsed radars in wideband scenarios is studied. To fulfil the need for frequency and position finding, the proposed receiver employs a three-dimensional antenna array, followed by radio-frequency back-end and ADC blocks, inspired by the modulated wideband converter technique. Furthermore, an algorithm based on Bayesian compressed sensing, incorporating off-grid techniques, is employed to jointly estimate the azimuth and the elevation angles of incoming signals, as well as their carrier frequencies. Simulation results are provided to support the theoretical results obtained in this study. The results show that the proposed off-grid Bayesian method has a significantly lower mean square estimation error than the conventional deterministic approaches, while its average computation complexity can be reduced in multi-snapshot scenarios.

关键词： direction-of-arrival estimation electronic warfare radar antennas antenna arrays radionavigation compressed sensing radar signal processing analogue-digital conversion radar receivers Bayes methods signal sampling mean square error methods joint frequency two-dimensional direction-of-arrival estimation ES systems subNyquist sampling electronic support receivers wide instantaneous bandwidth wide-frequency range modern radar signals analogue-to-digital converters high sampling rates digital ES receivers back-end ADC system-level approach required digitisation rate minimisation compressive sampling location finding pulsed radars frequency finding position finding three-dimensional antenna array ADC blocks modulated wideband converter technique Bayesian compressed sensing off-grid techniques joint azimuth estimation joint elevation angles estimation off-grid Bayesian method mean square estimation error computation complexity multisnapshot scenarios electronic warfare nomenclature

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An efficient key agreement and authentication protocol for secure communication in industrial IoT applications

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2021年第3期14卷 1431-1443页

作者： Vinoth, R. Deborah, Lazarus Jegatha Gojan Sch Business & Technol Dept Informat Technol Chennai 600052 Tamil Nadu India Univ Coll Engn Tindivanam Dept Comp Sci & Engn Tindivanam 604001 Tamil Nadu India

A most prominent and emerging technology namely the Internet of Things (IoT) enables legitimate users to access and monitor the sensors installed in various units of the industry. Such access and monitoring is facilitated using a secure authenticated key agreement (AKA) protocol. However, the complexity arises during the establishment of an effective session key agreement protocol to allow users to communicate securely with the sensors placed in the industrial IoT (IIoT). Few key agreement protocols existing in the literature have proved to perform the task effectively. Nevertheless, such protocols suffer from increased computation and communication cost. Hence, the motivation is to develop an efficient key agreement protocol that could over perform the existing protocols. Therefore, this research paper proposes an efficient key agreement protocol which is computationally and communication efficient. Moreover, the proposed key agreement protocol permits the users to securely communicate with the sensors. The proposed work focuses on twin dimensions. The first dimension is to reduce the computational complexity while sharing the mutual session key among the users and sensors. The second dimension focuses on decreasing the communicational cost. This is achieved by minimizing the amount of information communicated among the users and sensors. Subsequently, the proposed protocol is a hybrid methodology in which there are two working layers through which the session key is established. In the first layer, a mutual secret key is generated using a well-known elliptic curve cryptography (ECC) technique and this is shared among the users and the gateway node (GWN). In the second layer, the key generated in the above layer is used and the user initiates the key agreement process, wherein the GWN and sensors are generating a mutual session key using a group key. The simulated results of the proposed work clearly depicts the substantial reduction of computational and communicat

关键词： Industrial Internet of Things Authenticated key agreement computation complexity Communication cost Elliptic curve cryptography

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MULTIPROCESSOR IMPLEMENTATION OF REAL-TIME DSP ALGORITHMS

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 1995年第3期3卷 393-403页

作者： WANG, DJ HU, YH Dept. of Electr. & Comput. Eng. Wisconsin Univ. Madison WI USA

In this paper, we consider multiprocessor implementation of real-time recursive digital signal processing algorithms. The objective is to devise a periodic schedule, and a fully static task assignment scheme to meet the desired throughput rate while minimizing the number of processors. Toward this goal, we propose a notion called cutoff time, We prove that the minimum-processor schedule can be found within a finite time interval bounded by the cutoff time. As such the complexity of the scheduling algorithm and the allocation algorithm can be significantly reduced. Next, taking advantage of the cutoff time, we derive efficient heuristic algorithms which promise better performance and less computation complexity compared to other existing algorithms. Extensive benchmark examples are tested,which yield most encouraging results.

关键词： Real Time Systems Signal Processing Processor Scheduling Scheduling computational complexity Multiprocessing Systems Parallel Algorithms Resource Allocation Multiprocessor Implementation Real Time DSP Algorithms Recursive Digital Signal Processing Algorithms Periodic Schedule Fully Static Task Assignment Scheme Throughput Rate Cutoff Time Minimum Processor Schedule Allocation Algorithm Heuristic Algorithms computation complexity Digital Signal Processing Signal Processing Algorithms Processor Scheduling Throughput Sampling Methods Delay Scheduling Algorithm Heuristic Algorithms Benchmark Testing Real Time Systems

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