The discrimination algorithms for overlapped MPSK and MQAM modulations using higher-order cumulants

Automatic Modulation Classification (AMC) is responsible for detecting the correct modulation types in the intelligent receivers. AMC performance degrades when the signal-to-noise ratio (SNR) decreases because of the overlapping among the digital modulation types’ features, and this performance worsens under fading channel conditions. This paper proposes two new algorithms that improve the AMC performance accuracy of the overlapped digital modulations in feature space by improving their discrimination. These algorithms are named temporal Fisher discriminant analysis (TFDA) and supervised Fisher discriminant analysis (SFDA). The simulation results show that TFDA improves AMC performance accuracy up to 19.01% compared with the reference paper (Ge et al., 2021) and up to 38.15% compared with the reference paper (Teng et al., 2018). In contrast, SFDA improves AMC performance accuracy up to 23.12 % compared with the reference paper (Ge et al., 2021) and up to 49.025% compared with the reference paper (Teng et al., 2018).     

On the critical packet injection rate of a preferential next-nearest neighbor routing traffic model on Barabási-Albert networks

Recently, Yin et al. [Eur. Phys. J. B 49, 205 (2006)] introduced an efficient small-world network traffic model using preferential next-nearest neighbor routing strategy with the so-called path iteration avoidance (PIA) rule to study the jamming transition of internet. Here we study their model without PIA rule by a mean-field analysis which carefully divides the message packets into two types. Then, we argue that our mean-field analysis is also applicable in the presence of PIA rule in the limit of a large number of nodes in the network. Our analysis gives an explicit expression of the critical packet injection rate R_c as a function of a bias parameter of the routing strategy α in their model with or without PIA rule. In particular, we predict a sudden change in R_c at a certain value of α. These predictions agree quite well with our extensive computer simulations.     

Quantum key distribution protocol using dense coding of three-qubit W state

The three-qubit W state, with an important feature that each pair of it’s qubits has the same and maximum amount of bipartite entanglement, can be reduced to an entangled 2-qubit system if one of its qubits is lost. Recently, Xue et al. proposed a three-party quantum secret sharing (QSS) protocol based on the three-qubit W state [Chinese Phys. 15, 7 (2006)]. Also, Joo et al. proposed a pair-wise quantum key distribution protocol among three users based on a special measurement on the three-qubit W state [eprint arXiv:quant-ph/0204003v2 (2002)]. This study aims to propose a novel quantum key distribution protocol (QKDP) for arbitrary two communications based on the dense coding and the special measurement of three-qubit W state with the X basis and the Z basis.     

Analysis of stock prices of mining business

Stock exchanges have a diversity of so-called business groups and much evidence has been presented by covariance matrix analysis (Laloux et al. (1999) [6], Plerou et al. (2002) [7], Plerou et al. (1999) [8], Mantegna (1999) [9], Utsugi et al. (2004) [21] and Lim et al. (2009) [26]). A market-wide effect plays a crucial role in shifting the correlation structure from random to non-random. In this work, we study the structural properties of stocks related to the mining industry, especially rare earth minerals, listed on two exchanges, namely the TSX (Toronto stock exchange) and the TSX-V (Toronto stock exchange-ventures). In general, raw-material businesses are sensitively affected by the global economy while each firm has its own cycle. We prove that the global crisis during 2006–2009 affected the mineral market considerably. These two aspects compete to control price fluctuations. We show that the internal cycle overwhelms the global economic environment in terms of random matrix theory and overlapping matrices. However, during the period of 2006–2009, the effect of the global economic environment emerges. This result is well explained by the recent global financial/economic crisis. For comparison, we analyze the time stability of business clusters of the KOSPI, that is, the electric/electronic business, using an overlapping matrix. A clear difference in behavior is confirmed. Consequently, rare earth minerals in the raw-material business should be classified not by standard business classifications but by the internal cycle of business.     

Optimal symmetric networks in terms of minimizing average shortest path length and their sub-optimal growth model

Homogeneous entangled networks characterized by small world, large girths, and no community structure have attracted much attention due to some of their favorable performances. However, the optimization algorithm proposed by Donetti et al. is very time-consuming and will lose its efficiency when the size of the target network becomes large. In this paper, an alternative optimization algorithm is provided to get optimal symmetric networks by minimizing the average shortest path length. It is shown that the synchronizability of a symmetric network is enhanced when the average shortest path length of the network is shortened as the optimization proceeds, which suggests that the optimal symmetric networks in terms of minimizing average shortest path length will be very close to those entangled networks. In order to overcome the time-consuming obstacle of the optimization algorithms proposed by us and Donetti et al., a growth model is proposed to get large scale sub-optimal symmetric networks. Numerical simulations show that the symmetric networks derived by our growth model will have small-world property, and besides, these networks will have many other similar favorable performances as entangled networks, e.g., robustness against errors and attacks, very good load balancing ability, and strong synchronizability.     

Michaelis-Menten mechanism for single-enzyme and multi-enzyme system under stochastic noise and spatial diffusion

The investigation of enzymatic reaction under stochastic effect and spatial effect is an interesting problem. By virtue of Monte Carlo simulation, the stochastic dynamic of enzyme and the related Michaelis-Menten mechanism with stochastic internal noise and spatial diffusion are explored in this article. (i) For the single-enzyme system, two cases, including the fast phosphorylation case [X. S. Xie, et al., J. Phys. Chem. B 109 (2005) 19068] and slow phosphorylation case [X. S. Xie, et al., Nat. Chem. Biol. 2 (2006) 87] are considered. It is found the micro enzymatic velocity rate shows a rough hyperbolic dependence on the substrate concentration, hence obeys the Michaelis-Menten law qualitatively. In addition, our result reveals that diffusion rate can adjust the Michaelis-Menten curve; especially, it is shown that increasing diffusion rate enhances the micro enzyme rate. (ii) For the multi-enzyme system, a typical example, i.e., MAPK signaling pathway is used. We apply the Michaelis-Menten mechanism to the MAPK cascade and give a simple comparison for the signaling ability between the Michaelis-Menten mechanism and the single collision mechanism [J. W. Locasale et al., PLOS Comput. Biol. 4 (2008) e1000099].     

On the motif distribution in random block-hierarchical networks

The distribution of motifs in random hierarchical topological networks defined by nonsymmetric random block-hierarchical adjacency matrices, is constructed for the first time. According to the classification of U. Alon et al. of network superfamilies (Milo et al., 2004 [11]) by their motifs distributions, our artificial directed random hierarchical networks fall into the superfamily of natural networks to which the neuron networks belong. This is the first example of a class of “handmade” topological networks with the motifs distribution as in a special class of natural networks of essential biological importance.     

Are per capita incomes of MENA countries converging or diverging?

This study considers the issue of income convergence among the MENA (Middle East and North African) countries by using real per capita incomes over the period 1950-2006. We employed (Kapetanios et al. 2003) [21] unit root test by incorporating an additive constant and a trend component as Chong et al. (2008) [20] did in their study and found most of the MENA countries diverging during the sample period.     

Analysis of symmetry breaking in quartz blocks using superstatistical random-matrix theory

We study the symmetry breaking of acoustic resonances measured by Ellegaard et al. (1996) [1] in quartz blocks. The observed resonance spectra show a gradual transition from a superposition of two uncoupled components, one for each symmetry realization, to a single component that is well represented by a Gaussian orthogonal ensemble (GOE) of random matrices. We discuss the applicability of superstatistical random-matrix theory to the final stages of the symmetry-breaking transition. A comparison is made between the formula from superstatistics and that from a previous work by Abd El-Hady et al. (2002) [7], which describes the same data by introducing a third GOE component. Our results suggest that the inverse chi-squared superstatistics could be used for studying the whole symmetry-breaking process.     

Nonextensive analysis of seismic sequences

By using the Tsallis-based nonextensive statistics, the analysis of the magnitude distribution of several seismic catalogues in Italy was performed. The analysis shows similar values for the q-value, in good agreement with those obtained for other seismo-tectonic settings [e.g. Silva et al. (2006) [2] and Vilar et al. (2007) [3]]. In particular, it is shown that the volcano seismicity is characterized by slightly lower values for q. The latter results could provide hints for further investigation in discriminating tectonic from volcanic seismicity.     

Nonparametric Causal Structure Learning in High Dimensions

The PC and FCI algorithms are popular constraint-based methods for learning the structure of directed acyclic graphs (DAGs) in the absence and presence of latent and selection variables, respectively. These algorithms (and their order-independent variants, PC-stable and FCI-stable) have been shown to be consistent for learning sparse high-dimensional DAGs based on partial correlations. However, inferring conditional independences from partial correlations is valid if the data are jointly Gaussian or generated from a linear structural equation model—an assumption that may be violated in many applications. To broaden the scope of high-dimensional causal structure learning, we propose nonparametric variants of the PC-stable and FCI-stable algorithms that employ the conditional distance covariance (CdCov) to test for conditional independence relationships. As the key theoretical contribution, we prove that the high-dimensional consistency of the PC-stable and FCI-stable algorithms carry over to general distributions over DAGs when we implement CdCov-based nonparametric tests for conditional independence. Numerical studies demonstrate that our proposed algorithms perform nearly as good as the PC-stable and FCI-stable for Gaussian distributions, and offer advantages in non-Gaussian graphical models.     

DSP based receiver implementation for OFDM acoustic modems

Significant progress has been made recently on the use of multicarrier modulation in the form of orthogonal frequency division multiplexing (OFDM) for high data rate underwater acoustic communications. In this paper, we present implementation results of OFDM acoustic modems under different settings with either one or two parallel data streams transmitted, whose data rate is 3.2 KB/s or 6.4 KB/s, respectively, with QPSK modulation, rate-1/2 channel coding, and signal bandwidth of 6 kHz. To achieve real time operation, the processing time for each OFDM block shall be (much) less than the block duration of 210 ms. We first implement the receiver algorithms on a floating point TMS320C6713 DSP development board, running at 225 MHz. With convolutional coding, the per-block processing time is about 38 ms and 77 ms for single-input single-output (SISO) and multi-input multi-output (MIMO) settings, respectively, where there are two transmitters and two receivers in the latter case. With nonbinary low-density parity-check (LDPC) coding, which gains about 2 dB in error performance relative to convolutional coding, the per-block processing time increases to 50 ms and 101 ms for SISO and MIMO settings, respectively. We have also implemented the receiver algorithms using a fixed-point TMS320C6416 DSP development board, where the DSP core runs at 1 GHz. The per-block processing time reduces by two thirds with negligible performance degradation.     

Green functions and Langevin equations for nonlinear diffusion equations: A comment on ‘Markov processes, Hurst exponents, and nonlinear diffusion equations’ by Bassler et al.

We discuss two central claims made in the study by Bassler et al. [K.E. Bassler, G.H. Gunaratne, J.L. McCauley, Physica A 369 (2006) 343]. Bassler et al. claimed that Green functions and Langevin equations cannot be defined for nonlinear diffusion equations. In addition, they claimed that nonlinear diffusion equations are linear partial differential equations disguised as nonlinear ones. We review bottom-up and top-down approaches that have been used in the literature to derive Green functions for nonlinear diffusion equations and, in doing so, show that the first claim needs to be revised. We show that the second claim as well needs to be revised. To this end, we point out similarities and differences between non-autonomous linear Fokker-Planck equations and autonomous nonlinear Fokker-Planck equations. In this context, we raise the question whether Bassler et al.’s approach to financial markets is physically plausible because it necessitates the introduction of external traders and causes. Such external entities can easily be eliminated when taking self-organization principles and concepts of nonextensive thermostatistics into account and modeling financial processes by means of nonlinear Fokker-Planck equations.     

The Constituent Quark Exchange Model for the Bound State Nucleons

The aim of present article is to compare the different bound state parton distributions in the protons with those coming from the free protons experimental data and to investigate the effect of quark structure of protons on each other. So, the constituent quark model (CQM), in which the quarks are assumed to be the complex objects and was originally proposed by Altarelli et al. (ACMP), is used in the frame work of the quark exchange model (QEM) to calculate the parton distributions of bound protons. Unlike our previous works, the effect of sea quarks and gluons are included in the QEM. Our results are in agreement with those of Glück et al. (GRV) when we ignore the binding and the Fermi motion effects for the constituent quarks. In this case, we get more sea-quarks and gluons with respect to the bound state constituents quarks calculation. It is also shown that the QEM, which is a realistic formalism gives better result with respect to the Isgur and Karl et al. model which is a field theoretical approach. The ratio of the structure functions of neutron to proton is also calculated with the assumption of isospin symmetry and it is compared with the available data and our previous works.     

The Sasaki join and admissible Kähler constructions

We give a survey of our recent work (Boyer and Tønnesen-Friedman (2013) [50], [51], [30], Boyer and Tønnesen-Friedman (2014) [33], [29], [36]) describing a method which combines the Sasaki join construction of Boyer et al. (2007) [31] with the admissible Kähler construction of Apostolov et al. (2006, 2004, 2008) [26], [27], [14], [25] to obtain new extremal and new constant scalar curvature Sasaki metrics, including Sasaki–Einstein metrics. The constant scalar curvature Sasaki metrics also provide explicit solutions to the CR Yamabe problem. In this regard we give examples of the lack of uniqueness when the Yamabe invariant $\lambda \left(M\right)$ is positive.     

Studies on controllability of directed networks with extremal optimization

Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and attractive subjects for both network and control communities. In this paper, based on a given directed–weighted network with both state and control nodes, a novel optimization tool with extremal dynamics to generate an optimal network topology with minimum control nodes and complete controllability under Kalman’s rank condition has been developed. The experimental results on a number of popular benchmark networks show the proposed tool is effective to identify the minimum control nodes which are sufficient to guide the whole network’s dynamics and provide the evolution of network topology during the optimization process. We also find the conclusion: “the sparse networks need more control nodes than the dense, and the homogeneous networks need fewer control nodes compared to the heterogeneous” (Liu et al., 2011  [18]), is also applicable to network complete controllability. These findings help us to understand the network dynamics and make a real-world network under the desired control. Moreover, compared with the relevant research results on structural controllability with minimum driver nodes, the proposed solution methodology may also be applied to other constrained network optimization problems beyond complete controllability with minimum control nodes.     

Noncommutative Resolutions of ADE Fibered Calabi-Yau Threefolds

In this paper we construct noncommutative resolutions of a certain class of Calabi-Yau threefolds studied by Cachazo et al. (Geometric transitions and N = 1 quiver theories. , 2001). The threefolds under consideration are fibered over a complex plane with the fibers being deformed Kleinian singularities. The construction is in terms of a noncommutative algebra introduced by Ginzburg (Calabi-Yau algebras. , 2006) which we call the “N = 1 ADE quiver algebra”.     

Understanding the enhanced synchronization of delay-coupled networks with fluctuating topology

We study the dynamics of networks with coupling delay, from which the connectivity changes over time. The synchronization properties are shown to depend on the interplay of three time scales: the internal time scale of the dynamics, the coupling delay along the network links and time scale at which the topology changes. Concentrating on a linearized model, we develop an analytical theory for the stability of a synchronized solution. In two limit cases, the system can be reduced to an “effective” topology: in the fast switching approximation, when the network fluctuations are much faster than the internal time scale and the coupling delay, the effective network topology is the arithmetic mean over the different topologies. In the slow network limit, when the network fluctuation time scale is equal to the coupling delay, the effective adjacency matrix is the geometric mean over the adjacency matrices of the different topologies. In the intermediate regime, the system shows a sensitive dependence on the ratio of time scales, and on the specific topologies, reproduced as well by numerical simulations. Our results are shown to describe the synchronization properties of fluctuating networks of delay-coupled chaotic maps.     

Comment on ‘An optimal algorithm for counting networks motifs’ [Physica A 381 (2007) 482-490]

Network motifs in a given network are small connected subnetworks that occur at significantly higher frequencies than would be expected for a random network. In their 2007 article “An optimal algorithm for counting network motifs”, Itzhack, Mogilevski, and Louzoun present an algorithm for detecting network motifs. Based on an experimental comparison with a motif detection software called FANMOD, they claim that their algorithm is “more than a thousand times faster” than any previous motif detection algorithm. We show that this claim is not correct and based on a significant flaw in the experimental setup. Once the experimental data of Itzhack et al. is corrected for this flaw, the implementation of their algorithm actually turns out to be a little slower than FANMOD for random Erd?s-Rényi graphs. For random scale-free networks, the implementation of Itzhack et al. is faster only by a factor of ∼1.5, not the orders of magnitude claimed by Itzhack et al.     

Kinetic Models with Randomly Perturbed Binary Collisions

We introduce a class of Kac-like kinetic equations on the real line, with general random collisional rules which, in some special cases, identify models for granular gases with a background heat bath (Carrillo et al. in Discrete Contin. Dyn. Syst. 24(1):59–81, 2009), and models for wealth redistribution in an agent-based market (Bisi et al. in Commun. Math. Sci. 7:901–916, 2009). Conditions on these collisional rules which guarantee both the existence and uniqueness of equilibrium profiles and their main properties are found. The characterization of these stationary states is of independent interest, since we show that they are stationary solutions of different evolution problems, both in the kinetic theory of rarefied gases (Cercignani et al. in J. Stat. Phys. 105:337–352, 2001; Villani in J. Stat. Phys. 124:781–822, 2006) and in the econophysical context (Bisi et al. in Commun. Math. Sci. 7:901–916, 2009).