$$\ell _{1/2,1}$$ group sparse regularization for compressive sensing

Recently, the design of group sparse regularization has drawn much attention in group sparse signal recovery problem. Two of the most popular group sparsity-inducing regularization models are \(\ell _{1,2}\) and \(\ell _{1,\infty }\) regularization. Nevertheless, they do not promote the intra-group sparsity. For example, Huang and Zhang (Ann Stat 38:1978–2004, 2010) claimed that the \(\ell _{1,2}\) regularization is superior to the \(\ell _1\) regularization only for strongly group sparse signals. This means the sparsity of intra-group is useless for \(\ell _{1,2}\) regularization. Our experiments show that recovering signals with intra-group sparse needs more measurements than those without, by the \(\ell _{1,\infty }\) regularization. In this paper, we propose a novel group sparsity-inducing regularization defined as a mixture of the \(\ell _{1/2}\) norm and the \(\ell _{1}\) norm, referred to as \(\ell _{1/2,1}\) regularization, which can overcome these shortcomings of \(\ell _{1,2}\) and \(\ell _{1,\infty }\) regularization. We define a new null space property for \(\ell _{1/2,1}\) regularization and apply it to establish a recoverability theory for both intra-group and inter-group sparse signals. In addition, we introduce an iteratively reweighted algorithm to solve this model and analyze its convergence. Comprehensive experiments on simulated data show that the proposed \(\ell _{1/2,1}\) regularization is superior to \(\ell _{1,2}\) and \(\ell _{1,\infty }\) regularization.     

$$L_{1}$$-norm constrained normalized subband adaptive filter algorithm with variable norm-bound parameter and improved version

The \(L_{1}\)-norm constrained normalized subband adaptive filter with variable norm-bound parameter \((L_{1}\hbox {NCNSAF-V})\) algorithm and its variable step size version VSS-\(L_{1}\)NCNSAF-V are proposed in this paper, which are more superior to some existing algorithms in the sparse system. The proposed \(L_{1}\)NCNSAF-V is derived by using the Lagrange multiplier method, and the VSS-\(L_{1}\)NCNSAF-V is obtained by minimizing the statistical square of the Euclidean norm of the noise-free subband a posterior error vector. The simulation results demonstrate that the proposed algorithms achieve good performance.     

Theoretical Prediction of an Antimony-Silicon Monolayer $$(\hbox {penta-Sb}_{2}\hbox {Si})$$: Band Gap Engineering by Strain Effect

In this paper, using a first principles calculation, a two-dimensional structure of silicon-antimony named penta-Sb\(_{2}\)Si is predicted. The structural, kinetic, and thermal stabilities of the predicted monolayer are confirmed by the cohesive energy calculation, phonon dispersion analysis, and first principles molecular dynamic simulation, respectively. The electronic properties investigation shows that the pentagonal Sb\(_{2}\)Si monolayer is a semiconductor with an indirect band gap of about 1.53 eV (2.1 eV) from GGA-PBE (PBE0 hybrid functional) calculations which can be effectively engineered by employing external biaxial compressive and tensile strain. Furthermore, the optical characteristics calculation indicates that the predicted monolayer has considerable optical absorption and reflectivity in the ultraviolet region. The results suggest that a Sb\(_{2}\)Si monolayer has very good potential applications in new nano-optoelectronic devices.     

Generalized $${\varvec{H}_{\infty }}$$ model reduction for stable two-dimensional discrete systems

For model reduction, the approximation performance sometimes needs to be enhanced over a specific frequency range. Motivated by this fact, the paper investigates generalized \(H_{\infty }\) model reduction for stable two-dimensional (2-D) discrete systems represented by the Roesser model and the Fornasini–Machesini local state-space model, respectively. The generalized \(H_{\infty }\) norm of 2-D systems is introduced to evaluate the approximation error over a specific finite frequency (FF) domain. In light of the 2-D generalized Kalman–Yakubovich–Popov lemmas, sufficient conditions in terms of linear matrix inequalities are derived for the existence of a stable reduced-order model satisfying a specified generalized \(H_{\infty }\) level. Several examples are provided to illustrate the effectiveness and advantages of the proposed method. Compared with most of the existing 2-D model reduction results, the proposed method has the following merits: (1) The generalized \(H_\infty \) model reduction problems are considered for both important types of 2-D models, and no structural assumption is made for the plant model, so that our method has a broader applicable scope. (2) The reduced-order model is guaranteed to be stable, and an upper bound on the generalized \(H_{\infty }\) error is provided. Moreover, no frequency weighting function is needed. (3) The proposed method is applicable for 2-D model reduction with multiple FF specifications.     

Direction of arrival estimation via reweighted $$l_1$$ norm penalty algorithm for monostatic MIMO radar

In this paper, a reweighted \(l_1\) norm penalty algorithm for direction of arrival (DOA) estimation in monostatic multiple-input multiple-output radar is proposed. In the proposed method, exploiting the inherent multidimensional structure of received data after matched filtering, the singular value decomposition (SVD) technique of the data matrix is employed to reduce the dimension of the received signal. Then a novel weight matrix is designed for reweighting the \(l_1\) norm minimization by exploiting the coefficients of the reduced-dimensional Capon (RD-Capon) spatial spectrum. The proposed algorithm enhances the sparsity of the solution by the reweighted \(l_1\) norm constraint minimization, and the DOAs can be estimated by finding the non-zero rows of the recovered matrix. Owing to utilizing the SVD technique and the novel weight matrix, the proposed algorithm can provide better angle estimation performance than RD-Capon and \(l_1\)-SRACV algorithms. Furthermore, it is suitable for coherent sources and has a low sensitivity to the incorrect determination of the source numbers. The effectiveness and superior performance of the proposed algorithm are demonstrated by numerical simulations.     

Effects of Multiple Stacking Faults on the Electronic and Optical Properties of Armchair MoS$$_{}$$ Nanoribbons: First-Principles Calculations

The electronic and optical properties of armchair MoS\(_{2}\) nanoribbons with multiple stacking faults are investigated using first-principles calculations. It’s interesting that the band gaps approach zero for armchair MoS\(_{2}\) nanoribbons with two and four stacking faults. The gaps of armchair MoS\(_{2}\) nanoribbons with one stacking fault and three stacking faults are converged to 0.46 eV and 0.36 eV, respectively, which is smaller than perfect MoS\(_{2}\) nanoribbons. The partial charge density of armchair MoS\(_{2}\) nanoribbons with two stacking faults shows that the defect levels are originated from stacking faults. The frequency-dependent optical response (dielectric function, absorption, reflectance and electron energy loss spectra) is also presented. The optical results of monolayer MoS\(_{2}\) are in agreement with previous study. The peaks in the imaginary part of perfect armchair MoS\(_{2}\) nanoribbons are about 2.8 eV, 4.0 eV and 5.4 eV and the peaks of the imaginary part of armchair MoS\(_{2}\) nanoribbons with stacking faults are mainly 2.8 eV and 5.4 eV. They are independent of ribbon width. The peaks in electron energy loss spectra move toward larger wavelengths (redshift) due to the introduction of stacking faults.     

A pruning ensemble model of extreme learning machine with $$L_{1/2}$$ regularizer

Extreme learning machine (ELM) as an emerging branch of machine learning has shown its good generalization performance at a very fast learning speed. Nevertheless, the preliminary ELM and other evolutional versions based on ELM cannot provide the optimal solution of parameters between the hidden and output layer and cannot determine the suitable number of hidden nodes automatically. In this paper, a pruning ensemble model of ELM with \(L_{1/2} \) regularizer (PE-ELMR) is proposed to solve above problems. It involves two stages. First, we replace the original solving method of the output parameter in ELM to a minimum squared-error problem with sparse solution by combining ELM with \(L_{1/2}\) regularizer. Second, in order to get the required minimum number for good performance, we prune the nodes in hidden layer with the ensemble model, which reflects the superiority in searching the reasonable hidden nodes. Experimental results present the good performance of our method PE-ELMR, compared with ELM, OP-ELM and PE-ELMR (L1), for regression and classification problems under a variety of benchmark datasets.     

Stabilization of Discrete-time Fuzzy Systems Via Delta Operators and its Application to Truck–Trailer Model

This paper addresses the problem of robust \(L_2{-}L_\infty \) control in delta domain for a class of Takagi–Sugeno (TS) fuzzy systems with interval time-varying delays and disturbance input. In particular, the system under study involves state time delay, uncertainties and fast sampling period \(\mathcal {T}\). The main aim of this work was to design a \(L_2{-}L_\infty \) controller such that the proposed TS fuzzy system is robustly asymptotically stable with a \(L_2{-}L_\infty \) prescribed performance level \(\gamma >0\). Based on the proper Lyapunov–Krasovskii functional (LKF) involving lower and upper bound of time delay and free-weighting technique, a new set of delay-dependent sufficient conditions in terms of linear matrix inequalities (LMIs) are established for obtaining the required result. The result reveals that the asymptotic stability is achieved quickly when the sampling frequency is high. Finally, a numerical example based on the truck–trailer model is given to demonstrate the effectiveness and potential of the proposed design technique.     

Analysis and Design of $$H_{\infty }$$ Controllers for 2D Singular Systems with Delays

The \(H_{\infty }\) control design problem is solved for the class of 2D discrete singular systems with delays. More precisely, the problem addressed is the design of state-feedback controllers such that the acceptability, internal stability and causality of the resulting closed-loop system are guaranteed, while a prescribed \(H_\infty \) performance level is simultaneously fulfilled. By establishing a novel version of the bounded real lemma, a linear matrix inequality condition is derived for the existence of these \(H_\infty \) controllers. They can then be designed by solving an iterative algorithm based on LMI optimizations. An illustrative example shows the applicability of the algorithm proposed.     

The $$\mathbb {}$$-curve Construction for Endomorphism-Accelerated Elliptic Curves

We give a detailed account of the use of \(\mathbb {Q}\)-curve reductions to construct elliptic curves over \(\mathbb {F}_{p^2}\) with efficiently computable endomorphisms, which can be used to accelerate elliptic curve-based cryptosystems in the same way as Gallant–Lambert–Vanstone (GLV) and Galbraith–Lin–Scott (GLS) endomorphisms. Like GLS (which is a degenerate case of our construction), we offer the advantage over GLV of selecting from a much wider range of curves and thus finding secure group orders when \(p\) is fixed for efficient implementation. Unlike GLS, we also offer the possibility of constructing twist-secure curves. We construct several one-parameter families of elliptic curves over \(\mathbb {F}_{p^2}\) equipped with efficient endomorphisms for every \(p > 3\), and exhibit examples of twist-secure curves over \(\mathbb {F}_{p^2}\) for the efficient Mersenne prime \(p = 2^{127}-1\).     

Sparse Least Logarithmic Absolute Difference Algorithm with Correntropy-Induced Metric Penalty

Sparse adaptive filtering algorithms are utilized to exploit system sparsity as well as to mitigate interferences in many applications such as channel estimation and system identification. In order to improve the robustness of the sparse adaptive filtering, a novel adaptive filter is developed in this work by incorporating a correntropy-induced metric (CIM) constraint into the least logarithmic absolute difference (LLAD) algorithm. The CIM as an \(l_{0}\)-norm approximation exerts a zero attraction, and hence, the LLAD algorithm performs well with robustness against impulsive noises. Numerical simulation results show that the proposed algorithm may achieve much better performance than other robust and sparse adaptive filtering algorithms such as the least mean p-power algorithm with \(l_{1}\)-norm or reweighted \(l_{1}\)-norm constraints.     

$$H_{\infty }$$ Performance Analysis of 2D Continuous Time-Varying Delay Systems

This paper deals with the problem of \(H_{\infty }\) performance analysis of 2D continuous time-varying delay systems described by Roesser model. Using a simple Lyapunov–Krasovskii functional, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities. The obtained result is then extended to the problem of \(H_{\infty }\) performance analysis. Several examples are provided in order to illustrate the effectiveness of our results.     

Ultra-Fast Current Mode Sense Amplifier for Small $$I_{\mathrm{CELL}}$$ SRAM in FinFET with Improved Offset Tolerance

In this paper, a novel, high-performance and robust sense amplifier (SA) design is presented for small \(I_\mathrm{CELLl}\) SRAM, using fin-shaped field effect transistors (FinFET) in 22-nm technology. The technique offers data-line-isolated current sensing approach. Compared with the conventional CSA (CCSA) and hybrid SA (HSA), the proposed current feed-SA (CF-SA) demonstrates 2.15\(\times \) and 3.02\(\times \) higher differential current, respectively, for \({V}_{\mathrm{DD}}\) of 0.6 V. Our results indicate that even at the worst corner, CF-SA can provide 2.23\(\times \) and 1.7\(\times \) higher data-line differential voltage compared with CCSA and HSA, respectively. Further, 66.89 and 31.47 % reductions in the cell access time are achieved compared to the CCSA and HSA, respectively, under similar \(I_\mathrm{CELLl}\) and bit-line and data-line capacitance. Statistical simulations have proved that the CF-SA provides high read yield with 32.39 and 22.24 % less \(\upsigma _{\mathrm{Delay}}\). It also offers a much better read effectiveness and robustness against the data-line capacitance as well as \({V}_{\mathrm{DD}}\) variation. Furthermore, the CF-SA is able to tolerate a large offset of the input devices, up to 80 mV at \({V}_{\mathrm{DD}}=0.6\hbox {V}\).     

Two-channel perfect reconstruction (PR) quadrature mirror filter (QMF) bank design using logarithmic window function and spline function

In this work, two-channel perfect reconstruction quadrature mirror filter (QMF) bank has been proposed based on the prototype filter using windowing method. A novel window function based on logarithmic function along with the spline function is utilized for the design of prototype filter. The proposed window has a variable parameter ‘\(\alpha \)’, which varies the peak side lobe level and rate of fall-off side lobe level which in turn affects the peak reconstruction error (PRE) and amplitude distortion (\(e_{am}\)) of the QMF bank . The transition width of the prototype is controlled by the spline function using the parameter ‘\(\mu \)’. The perfect reconstruction condition is satisfied by setting the cutoff frequency (\(\omega _{c}\)) of the prototype low-pass filter at ‘\(\pi /2\)’. The performance of the proposed design method has been evaluated in terms of mean square error in the pass band, mean square error in the stop band, first side lobe attenuation (\(A_{1}\)), peak reconstruction error (PRE) and amplitude error (\(e_{am}\)) for different values of ‘\(\alpha \)’ and ‘\(\mu \)’. The results are provided and compared with the existing methods.     

Intermittent Fault Diagnosability of Hyper Petersen Network

The problem of permanent fault diagnosis has been discussed widely, and the diagnosability of many well-known networks have been explored. Faults of a multiprocessor system generally include permanent and intermittent, with intermittent faults regarded as the most challenging to diagnose. In this paper, we investigate the intermittent fault diagnosability of hyper Petersen networks. First, we derive that an \(n\)-dimensional hyper Petersen network \(HP_{n}\) with fault-free edges is \((n - 1)_{i}\)-diagnosable under the PMC model. Then, we investigate the intermittent fault diagnosability of \(HP_{n}\) with faulty edges under the PMC model. Finally, we prove that an \(n\)-dimensional hyper Petersen network \(HP_{n}\) is \((n - 2)_{i}\)-diagnosable under the MM* model.     

Stability and $${L_{\infty }}$$-Gain Analysis for Positive Switched Systems with Time-Varying Delay Under State-Dependent Switching

This paper investigates the problems of stability and \({L_\infty }\)-gain analysis for a class of positive switched systems with time-varying delay. Attention is focused on designing a state-dependent switching rule such that the system satisfies a prescribed \({L_\infty }\)-gain performance level, where the proposed scheme does not require the switching instants to be known in advance. By constructing an appropriate co-positive type Lyapunov–Krasovskii functional, sufficient conditions for exponential stability with \({L_\infty }\)-gain performance of the underlying systems are derived. Furthermore, the stability along the switching surface is analyzed. Finally, two examples are presented to demonstrate the effectiveness of the proposed method.     

Study on the Effect of Mn,Zn, and Sb on Undercooling Behavior of Sn-Ag-Cu Alloys Using Differential Thermal Analysis

Differential thermal analysis (DTA) has been conducted on directionally solidified near-eutectic Sn-3.0 wt.%Ag-0.5 wt.%Cu (SAC), SAC \(+\) 0.2 wt.%Sb, SAC \(+\) 0.2 wt.%Mn, and SAC \(+\) 0.2 wt.%Zn. Laser ablation inductively coupled plasma mass spectroscopy was used to study element partitioning behavior and estimate DTA sample compositions. Mn and Zn additives reduced the undercooling of SAC from 20.4\(^\circ \hbox {C}\) to \(4.9^\circ \hbox {C}\) and \(2^\circ \hbox {C}\), respectively. Measurements were performed at cooling rate of \(10^\circ \hbox {C}\) per minute. After introducing 200 ppm \(\hbox {O}_2\) into the DTA, this undercooling reduction ceased for SAC \(+\) Mn but persisted for SAC \(+\) Zn.     

Ab␣Initio Study of Aluminium Impurity and Interstitial-Substitutional Complexes in Ge Using a Hybrid Functional (HSE)

The results of an ab?initio modelling of aluminium substitutional impurity (\({\hbox {Al}}_{\rm Ge}\)), aluminium interstitial in Ge [\({\hbox {I}}_{\rm Al}\) for the tetrahedral (T) and hexagonal (H) configurations] and aluminium interstitial-substitutional pairs in Ge (\({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\)) are presented. For all calculations, the hybrid functional of Heyd, Scuseria, and Ernzerhof in the framework of density functional theory was used. Defects formation energies, charge state transition levels and minimum energy configurations of the \({\hbox {Al}}_{\rm Ge}\), \({\hbox {I}}_{\rm Al}\) and \({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\) were obtained for ?2, ?1, 0, \(+\)1 and \(+\)2 charge states. The calculated formation energy shows that for the neutral charge state, the \({\hbox {I}}_{\rm Al}\) is energetically more favourable in the T than the H configuration. The \({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\) forms with formation energies of ?2.37 eV and ?2.32 eV, when the interstitial atom is at the T and H sites, respectively. The \({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\) is energetically more favourable when the interstitial atom is at the T site with a binding energy of 0.8 eV. The \({\hbox {I}}_{\rm Al}\) in the T configuration, induced a deep donor (\(+\)2/\(+1\)) level at \(E_{\mathrm {V}}+0.23\) eV and the \({\hbox {Al}}_{\rm Ge}\) induced a single acceptor level (0/?1) at \(E_{\mathrm {V}}+0.14\) eV in the band gap of Ge. The \({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\) induced double-donor levels are at \(E_{\rm V}+0.06\) and \(E_{\rm V}+0.12\) eV, when the interstitial atom is at the T and H sites, respectively. The \({\hbox {I}}_{\rm Al}\) and \({\hbox {I}}_{\rm Al}{\hbox {Al}}_{\rm Ge}\) exhibit properties of charge state-controlled metastability.