A novel topology and the design method are proposed for a wideband bandpass filter (BPF) with frequency-and attenuation-reconfigurable in-band notch by engineering the complex frequencies of transmission zeros. The pr...
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Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backb...
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Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.
From AI-assisted art creation to large language model (LLM)-powered ChatGPT, AI-generated contents and services are becoming a transforming force. It calls for the telecom industry to embrace the prospects of AIGC ser...
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Background: Changes on source code may propagate to distant code entities through various relationships, making related changes obligatory. Identifying change impacts is challenging due to the complexity of how change...
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Coverage hole restoration and connectivity is a typical problem for underwater wireless sensor networks. In underwater applications like underwater oilfield reservoirs, undersea minerals and monitoring etc., where nod...
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A new frequency diverse array (FDA) radar system is proposed for range estimation of a target using time-invariant beampattern. To illuminate a desired range, the transmit beampattern is optimized using the inverse fa...
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In the era of Industry 4.0, the integration of sophisticated monitoring and control technologies is essential for the reliability and efficiency of industrial equipment. This paper presents a deep neural network (DNN)...
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Time-synchronization (TS) formation control for unmanned surface vehicles (USVs) presents several advantages, including precise execution of tasks, broadened combat capabilities, and improved information fusion qualit...
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Time-synchronization (TS) formation control for unmanned surface vehicles (USVs) presents several advantages, including precise execution of tasks, broadened combat capabilities, and improved information fusion quality. To achieve this performance, a time-synchronized formation control method is presented that takes into account direct topology, external disturbances, and system uncertainties (EDSU). In contrast to prior formation control strategies, we introduce the formalized time-synchronized formation control framework, where all state components of the formation system concurrently converge to the equilibrium point at a uniform time constant, independently of their initial states. To counteract the EDSU, a fixed-time disturbance observer is designed to guarantee the convergence of all observer error components to zero. System stability is corroborated through the application of Lyapunov-like theory. Simulations and comparative experiments on three USVs are conducted to demonstrate the proposed method's superiority. IEEE
A novel approach defined by the artificial neural network (ANN) model trained by the improved Gauss-Newton in conjunction with a simulated annealing technique is used to control a step-up converter. To elucidate the s...
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In this article, an event-based neuroadaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network...
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