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In this paper, a new dynamical model of memristor-based switching networks (MSNs) with multi-links and mixed time-varying delays is proposed based on the real structure of neurons. We design a kind of switched intermittent pinning control law to realize the synchronization of the proposed MSNs which is flexible in lowering the control cost. With the key theory of the differential inclusions, some effective synchronization criteria are derived to ensure the asymptotic synchronization and the exponential synchronization between the drive and response networks. Finally, numerical simulations demonstrate the correctness of our results.

Based on variable substitution, calculating definite integral and solving the minimization problem, in this paper we establish a new fixed-time stability theorem, which can provide a novel upper bound estimate formula for the settling time. By dividing the considered complex-valued neural networks (CVNNs) into double-layer real-valued neural networks, the fixed-time synchronization of CVNNs is analyzed by means of the new fixed-time stability theorem. Both theoretical derivation and numerical simulation show the new upper bound estimate formula for the settling time in this paper is more accurate than that given in the classic fixed-time stability theorem. A numerical example is given to verify the effectiveness of the main results.

This paper presents an LTE MIMO closed slot antenna system for laptops with a metal cover. Its main and auxiliary antennas have the same structure that measures 130 × 3 mm2. They are configured in a manner of reflection symmetry on the display metallic ground plane and are 5 mm away from the hinge. The distance between the two antennas is 20 mm, and the profile height of the MIMO antenna system is only 3 mm. This LTE closed slot antenna is excited by an exciter of 30 × 3 mm2 to cover the LTE eight-band operation (LTE700/GSM850/900/1800/1900/UMTS/LTE2300/2500). The exciter is a simple planar inverted-F antenna (PIFA) structure loaded with reactive matching elements, which can enhance the impedance matching in the desired frequency bands. This LTE MIMO closed slot antenna system has good isolation of at least 16 dB without adding any additional isolation elements. The measured antenna efficiency of the MIMO antenna system is larger than 40% in the low-frequency band and 50% in the high-frequency band, meeting the practical application requirements.

Identifying influential nodes in complex networks is of great significance. During recent decades, numerous methods regarding influential nodes identification or important nodes ranking have been developed. However, most of the existing methods either have low ranking accuracy or cannot be extended to large-scale networks. To address these issues, we propose a novel greedy algorithm named backward generating networks (BGNs) to identify influential nodes more accurately and more efficiently. BGN seeks to get the order of importance of nodes by minimizing the unique robustness value, which is an effective and brand-new metric to evaluate the importance of each node locally or the entire ranking results globally. The unique robustness measurement is rooted in the well-known percolation theory that with a certain fraction of nodes in a network being removed, the network collapses as much as possible. That is, the giant connected component in the collapsed network gets as small as possible. Therefore, BGN aims at finding a node sequence such that the giant connected component reduces in the steepest way. To this end, instead of deleting nodes from the network forwardly, BGN chooses to reconstruct the network by gradually adding nodes to an empty network according to the requirement that the giant connected component grows as slow as possible. We further propose heap-BGN to speed up BGN, and initial-BGN to make BGN produce more accurate results by proper initial rankings. Extensive experiments on four real-world networks and four synthetic networks demonstrate that BGN can outperform the state-of-the-art baseline algorithms, in terms of both ranking accuracy and computational efficiency.

This paper investigates the lag synchronization of memristive neural networks (MNNs) with mixed delays via adaptive control. Based on the switching jump properties of memristors and the assumption that the activation functions are bounded, three lemmas are derived first to deal with the theoretical analysis difficulties caused by the existences of time delays and time lag. By designing a series of suitable adaptive controllers, we prove that the considered MNNs can achieve asymptotic lag synchronization, exponential lag synchronization, and finite-time lag synchronization, respectively. Adaptive control can avoid the large control gains very well, and adaptive control can be used even when the system parameters are unknown. Moreover, extra calculations are not required to determine the appropriate control gains. Numerical simulations are presented to verify the effectiveness of the obtained theoretical results.

The shorted monopoles and the planar inverted-F antennas have been utilized for wireless local area network (WLAN) notebook applications for years. This paper presents an alternative and yet promising antenna type with a compact and smaller size of 5 mm $\times20$ mm to operate in the 2.4 GHz (2400–2484 MHz), 5.2 GHz (5150–5350 MHz), and 5.8 GHz (5725–5825 MHz) WLAN bands. The loop antenna, formed on a 0.4-mm-thick FR4 substrate, was adopted in this study. The loop radiator comprised a capacitively-driven feed and an end-loaded inductor. The capacitively-driven feed allowed the antenna to generate the quarter-wavelength loop resonance for possible lowest resonant mode excitation in addition to the loop’s half-wavelength mode. By loading an inductor at the loop end to be connected to the small antenna ground, the operating frequencies of the quarter- and half-wavelength resonances were further decreased to cover the 2.4 and 5.2/5.8 GHz bands with good input impedance therein.

This paper introduces a multiple-input and multiple-output (MIMO) antenna system for deployment in the closed hinge slot region of notebook computers for long-term evolution (LTE)/wireless wide area network (WWAN)/wireless local area network (WLAN) applications. This antenna system was placed in the closed hinge slot region formed by the full metal cover, metal ground plate, and metal hinges. The MIMO antenna system, includes a main antenna (Ant 1), an auxiliary antenna (Ant 2), and an isolation element. The main and auxiliary antennas were integrated with the metal surrounding them and were used to excite several resonance modes of the closed hinge slot. Excellent antenna efficiency was achieved using the small antennas. Although Ant1 and Ant2 are only 25 mm $\times5$ mm in size, they could cover LTE/WWAN or WLAN operating bands by switching feed points in the same antenna pattern. The isolation element—a 10 mm $\times6$ mm metal sheet—was placed at the center of the closed hinge slot region, and enhanced isolation by more than 7 dB. The isolation levels exceeded 18 dB for LTE700/2300/2500 bands and 15 dB for 2.4/5.2/5.8 GHz WLAN bands.