In this paper, one new class of quaternary generalized cyclotomic sequences with the period 2pq over F4 is established. The linear complexity of proposed sequences with the period 2pq is determined. The results show that such sequences have high linear complexity.

Multiple access (MA) technology is of most importance for beyond long term evolution (LTE) system. Non-orthogonal multiple access (NOMA) utilizing power domain and advanced receiver has been considered as a candidate MA technology recently. In this paper, power assignment method, which plays a key role in performance of NOMA, is investigated. The power assignment on the basis of maximizing geometric mean user throughput requires exhaustive search and thus has an unacceptable computational complexity for practical systems. To solve this problem, a novel power assignment method is proposed by exploiting tree search and characteristic of serial interference cancellation (SIC) receiver. The proposed method achieves the same performance as the exhaustive search while greatly reduces the computational complexity. On the basis of the proposed power assignment method, the performance of NOMA is investigated by link-level and system-level simulations in order to provide insight into suitability of using NOMA for future MA. Simulation results verify effectiveness of the proposed power assignment method and show NOMA is a very promising MA technology for beyond LTE system.

In this paper, we consider the optimization of measurement matrix in Compressed Sensing (CS) framework. Based on the boundary constraint, we propose a novel algorithm to make the “mutual coherence” approach a lower bound. This algorithm is implemented by using an iterative strategy. In each iteration, a neighborhood interval of the maximal off-diagonal entry in the Gram matrix is scaled down with the same shrinkage factor, and then a lower mutual coherence between the measurement matrix and sparsifying matrix is obtained. After many iterations, the magnitudes of most of off-diagonal entries approach the lower bound. The proposed optimization algorithm demonstrates better performance compared with other typical optimization methods, such as t-averaged mutual coherence. In addition, the effectiveness of CS can be used for the compression of complex synthetic aperture radar (SAR) image is verified, and experimental results using simulated data and real field data corroborate this claim.

Pyramid is a solitaire game, where the object is to remove all cards from both a pyramidal layout and a stock of cards. Two exposed cards can be matched and removed if their values total 13. Any exposed card of value 13 and the top card of the stock can be discarded immediately. We prove that the generalized version of Pyramid is NP-complete.

This paper proposes novel robust speech F0 estimation using Summation Residual Harmonics (SRH) based on TV-CAR (Time-Varying Complex AR) analysis. The SRH-based F0 estimation was proposed by A. Alwan, in which the criterion is calculated from LP residual signals. The criterion is summation of residual spectrum value for harmonics. In this paper, we propose SRH-based F0 estimation based on the TV-CAR analysis, in which the criterion is calculated from the complex AR residual. Since complex AR residual provides higher resolution of spectrum, it can be considered that the criterion is effective for F0 estimation. The experimental results demonstrate that the proposed method performs better than conventional methods; weighted auto-correlation and YIN.

The relationship between different brain areas is characterized by functional networks through correlations of time series obtained from neuroimaging experiments. Due to its high spatial resolution, functional MRI data is commonly used for generating functional networks of the entire brain. These networks are comprised of the measurement points/channels as nodes and links are established if there is a correlation in the measured time series of these nodes. However, since the evaluation of correlation becomes more accurate with the length of the underlying time series, we construct in this paper functional networks from MEG data, which has a much higher time resolution than fMRI. We study in particular how the network topologies change in an experiment on ambiguity of words, where the subject first receives a priming word before being presented with an ambiguous or unambiguous target word.

Many fatal accidents involving safety-critical reactive systems have occurred in unexpected situations, which were not considered during the design and test phases of system development. To prevent such accidents, reactive systems should be designed to respond appropriately to any request from an environment at any time. Verifying this property during the specification phase reduces the development costs of safety-critical reactive systems. This property of a specification is commonly known as realizability. The complexity of the realizability problem is 2EXPTIME-complete. We have introduced the concept of strong satisfiability, which is a necessary condition for realizability. Many practical unrealizable specifications are also strongly unsatisfiable. In this paper, we show that the complexity of the strong satisfiability problem is EXPSPACE-complete. This means that strong satisfiability offers the advantage of lower complexity for analysis, compared to realizability. Moreover, we show that the strong satisfiability problem remains EXPSPACE-complete even when only formulae with a temporal depth of at most 2 are allowed.

This paper presents a Complex-Valued Neural Network-based sound localization method. The proposed approach uses two microphones to localize sound sources in the whole horizontal plane. The method uses time delay and amplitude difference to generate a set of features which are then classified by a Complex-Valued Multi-Layer Perceptron. The advantage of using complex values is that the amplitude information can naturally masks the phase information. The proposed method is analyzed experimentally with regard to the spectral characteristics of the target sounds and its tolerance to noise. The obtained results emphasize and confirm the advantages of using Complex-Valued Neural Networks for the sound localization problem in comparison to the traditional Real-Valued Neural Network model.

This paper contributes to k-error linear complexity of some generalized cyclotomic binary sequences of length 2pm and pm constructed in recent years. By defining related reference sequences, we find that these sequences possess very low k-error linear complexity for some certain values of the parameter k even though they have high linear complexity. Moreover, we point out that (p-1)-tuple distributions of all these sequences are not span. Thus they should be selected carefully for use in stream cipher systems.

Binary sequences with low autocorrelation have important applications in communication systems and cryptography. In this paper, the autocorrelation values of binary Whiteman generalized cyclotomic sequences of order six and period pq are discussed. Our result shows that the autocorrelation of these sequences is four-valued and that the corresponding values are in {-1,3,-5,pq} if the parameters are chosen carefully.

In this paper, Hermite polynomial representation is proposed as an alternative way to represent finite fields of characteristic two. We show that multiplication in Hermite polynomial representation can be achieved with subquadratic space complexity. This representation enables us to find binomial or trinomial irreducible polynomials which allows us faster modular reduction over binary fields when there is no desirable such low weight irreducible polynomial in other representations. We then show that the product of two elements in Hermite polynomial representation can be performed as Toeplitz matrix-vector product. This representation is very interesting for NIST recommended binary field GF(2571) since there is no ONB for the corresponding extension. This representation can be used to obtain more efficient finite field arithmetic.

In the recently developed Flexible Wireless System (FWS), the same platform needs to deal with different wireless systems. This increases nonlinear distortion in its wideband power amplifier (PA) because the PA needs to concurrently amplify multi-band signals. By taking higher harmonics as well as inter- and cross-modulation distortion into consideration, we have developed a method to analytically evaluate the adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) on the basis of the PA's nonlinear characteristics. We devise a novel method for modeling the PA amplifying dual-band signals. The method makes it possible to model it merely by performing a one-tone test, making use of the Volterra series expansion and the general Wiener model. We then use the Mehler formula to derive the closed-form expressions of the PA's output power spectral density (PSD), ACPR, and EVM. The derivations are based on the assumption that the transmitted signals are complex Gaussian distributed in orthogonal frequency division multiplexing (OFDM) transmission systems. We validate the method by comparing measurement and simulation results and confirm it can appropriately predict the ACPR and EVM performance of the nonlinear PA output with OFDM inputs. In short, the method enables correct modeling of a wideband PA that amplifies dual-band signals merely by conducting a one-tone test.

Clustering methods are divided into hierarchical clustering, partitioning clustering, and more. K-Means is a method of partitioning clustering. We improve the performance of a K-Means, selecting the initial centers of a cluster through a calculation rather than using random selecting. This method maximizes the distance among the initial centers of clusters. Subsequently, the centers are distributed evenly and the results are more accurate than for initial cluster centers selected at random. This is time-consuming, but it can reduce the total clustering time by minimizing allocation and recalculation. Compared with the standard algorithm, F-Measure is more accurate by 5.1%.

This paper introduces the concept of order complexity, which represents the minimum number of partial ordering operations to make a string of perfectly ordered symbols. A novel variable-length code expressing such order complexity using binary digits is proposed herein. The proposed code is general, uniquely decipherable, and useful for coding a string of random permuted symbols having unknown statistics or which are preferred to have a uniform distribution.

Binary sequences with good autocorrelation and large linear complexity have found many applications in communication systems. A construction of almost difference sets was given by Cai and Ding in 2009. Many classes of binary sequences with three-level autocorrelation could be obtained by this construction and the linear complexity of two classes of binary sequences from the construction have been determined by Wang in 2010. Inspired by the analysis of Wang, we deternime the linear complexity and the minimal polynomials of another class of binary sequences, i.e., the class based on the WG difference set, from the construction by Cai and Ding. Furthermore, a generalized version of the construction by Cai and Ding is also presented.

One major challenge to implement orthogonal frequency division multiplexing (OFDM) systems over doubly selective channels is the non-negligible intercarrier interference (ICI), which significantly degrades the system performance. Existing solutions to cope with ICI include zero-forcing (ZF), minimum mean square error (MMSE) and other linear or nonlinear equalization methods. However, these schemes fail to achieve a satisfactory tradeoff between performance and computational complexity. To address this problem, in this paper we propose two novel nonlinear ICI cancellation techniques, which are referred to as parallel interference cancelation (PIC) and hybrid interference cancelation (HIC). Taking advantage of the special structure of basis expansion model (BEM) based channel matrices, our proposed schemes enjoy low computational complexity and are capable of cancelling ICI effectively. Moreover, since the proposed schemes can flexibly select different basis functions and be independent of the channel statistics, they are applicable to practical OFDM based systems such as DVB-T2 over doubly selective channels. Theoretical analysis and simulation results both confirm their performance-complexity advantages in comparison with some existing methods.

The linear complexity of quaternary sequences plays an important role in cryptology. In this paper, the minimal polynomial of a class of quaternary sequences with low autocorrelation constructed by generalized cyclotomic sequences pairs is determined, and the linear complexity of the sequences is also obtained.

In this letter, we first introduce a new generalized cyclotomic sequence of order two of length pq, then we calculate its linear complexity and minimal polynomial. Our results show that this sequence possesses both high linear complexity and optimal balance on 1 s and 0 s, which may be attractive for use in stream cipher cryptosystems.

Many deterministic small-world network models have been proposed so far, and they have been proven useful in describing some real-life networks which have fixed interconnections. Search efficiency is an important property to characterize small-world networks. This paper tries to clarify how the search procedure behaves when random walks are performed on small-world networks, including the classic WS small-world network and three deterministic small-world network models: the deterministic small-world network created by edge iterations, the tree-structured deterministic small-world network, and the small-world network derived from the deterministic uniform recursive tree. Detailed experiments are carried out to test the search efficiency of various small-world networks with regard to three different types of random walks. From the results, we conclude that the stochastic model outperforms the deterministic ones in terms of average search steps.

A variety of ubiquitous computing devices, such as radio frequency identification (RFID) and wireless sensor network (WSN), are generating huge and significant events that should be rapidly processed for business excellence. In this paper, we describe how complex event processing (CEP) technology can be applied to ubiquitous process management based on context-awareness. To address the issue, we propose a method for context-aware event processing using event processing language (EPL) statement. Specifically, the semantics of a situation drive the transformation of EPL statement templates into executable EPL statements. The proposed method is implemented in the domain of ubiquitous cold chain logistics management. With the proposed method, context-aware event processing can be realized to enhance business performance and excellence in ubiquitous computing environments.