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To fully display the modeling mechanism of the novel fractional order grey model (FGM (q,1)), this paper decomposes the data matrix of the model into the mean generation matrix, the accumulative generation matrix and the raw data matrix, which are consistent with the fractional order accumulative grey model (FAGM (1,1)). Following this, this paper decomposes the accumulative data difference matrix into the accumulative generation matrix, the q-order reductive accumulative matrix and the raw data matrix, and then combines the least square method, finding that the differential order affects the model parameters only by affecting the formation of differential sequences. This paper then summarizes matrix decomposition of some special sequences, such as the sequence generated by the strengthening and weakening operators, the jumping sequence, and the non-equidistance sequence. Finally, this paper expresses the influences of the raw data transformation, the accumulation sequence transformation, and the differential matrix transformation on the model parameters as matrices, and takes the non-equidistance sequence as an example to show the modeling mechanism. [ABSTRACT FROM AUTHOR]

This paper studies a cold standby repairable system with working vacations and vacation interruption. The repairman's multiple vacations policy, the working vacations policy and the vacation interruption are considered simultaneously. The lifetime of components follows a phase-type (PH) distribution. The repair time in the regular repair period and the working vacation period follow other two PH distributions at different rates. For this system, the vector-valued Markov process governing the system is constructed. We obtain several important performance measures for the system in transient and stationary regimes applying matrixanalytic methods. Finally, a numerical example is given to illustrate the results obtained. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of joint angle and delay estimation (JADE) in a multipath communication scenario. A low-complexity multi-way compressive sensing (MCS) estimation algorithm is proposed. The received data are firstly stacked up to a trilinear tensor model. To reduce the computational complexity, three random compression matrices are individually used to reduce each tensor to a much smaller one. JADE then is linked to a low-dimensional trilinear model. Our algorithm has an estimation performance very close to that of the parallel factor analysis (PARAFAC) algorithm and automatic pairing of the two parameter sets. Compared with other methods, such as multiple signal classification (MUSIC), the estimation of signal parameters via rotational invariance techniques (ESPRIT), the MCS algorithm requires neither eigenvalue decomposition of the received signal covariance matrix nor spectral peak searching. It also does not require the channel fading information, which means the proposed algorithm is blind and robust, therefore it has a higher working efficiency. Simulation results indicate the proposed algorithm have a bright future in wireless communications. [ABSTRACT FROM AUTHOR]

With progression of the digital age, the complexity of software continues to grow. As a result, methods to quantitatively assess characteristics of software have attracted significant attention. These efforts have led to a large number of new measures such as coupling metrics, many of which seek to consider the impact of correlations between components and failures on application reliability. However, most of these approaches set the coupling parameters arbitrarily by making assumptions instead of utilizing experimental data and therefore may not accurately capture actual coupling between components of software application. Since the coupling matrix is often set arbitrarily, the existing approaches to assess software reliability considering component correlation fail to reflect the real degree of interaction and relationships among software components. This paper presents an efficient approach to assess the software reliability considering correlated component failures, incorporating software architecture while considering actual internal coupling of software with an efficient approach based on multivariate Bernoulli (MVB) distribution. The unified framework for software coupling measurement is informed by a comprehensive survey of frameworks for objectoriented and procedure-oriented software. This framework enables the extraction of more accurate coupling among components. The effectiveness of this method is illustrated through an experimental study by applying it to a real-time software application. [ABSTRACT FROM AUTHOR]

The TODIM (an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making (MADM) problems considering the behavior of the decision maker (DM), while it cannot be used to handle the problem with unknown weight information on attributes, in this paper, a novel method based on the classical TODIM method is proposed to solve the hybrid MADM problems with unknown weight information on attributes, in which attribute values are represented in four different formats: crisp numbers, interval numbers, triangular fuzzy numbers and trapezoidal fuzzy numbers. Firstly, the positive-ideal alternative and negative-ideal alternative are determined, and the gain and loss matrices are constructed by calculating the gain and loss of each alternative relatived to the ideal alternatives concerning each attribute based on different distance calculation formulas, which may avoid the information missing or information distortion in the process of unifying multiform attribute values into a certain representation form. Secondly, an optimization model based on the maximizing deviation (MD) method, by which the attribute weights can be determined, is established for the TODIM method. Further, the calculation steps to solve the hybrid MADM problems are given. Finally, two numerical examples are presented to illustrate the usefulness of the proposed method, and the results show that the DM's psychological behavior, attribute weights and the transformed information would highly affect the ranking orders of alternatives. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of the direction of arrival (DOA) estimation under the compressive sampling (CS) framework. A novel approach, modified multiple signal classification (MMUSIC) based on the CS array (CSA-MMUSIC), is proposed to resolve the DOA estimation of correlated signals and two closely adjacent signals. By using two random CS matrices, a large size array is compressed into a small size array, which effectively reduces the number of the front end circuit. The theoretical analysis demonstrates that the proposed approach has the advantages of low computational complexity and hardware structure compared to other MMUSIC approaches. Simulation results show that CSA-MMUSIC can possess similar angular resolution as MMUSIC. [ABSTRACT FROM AUTHOR]

Firstly, the research progress of grey model GM (1,1) is summarized, which is divided into three development stages: assimilation, alienation and melting stages. Then, the matrix analysis theory is used to study the modeling mechanism of GM (1,1), which decomposes the modeling data matrix into raw data transformation matrix, accumulated generating operation matrix and background value selection matrix. The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM (1,1). Finally, the paper proposes a generalization grey model GGM (1,1), which is a extended form of GM (1,1) and also a unified form of model GM (1,1), model GM (1,1,α), stage grey model, hopping grey model, generalized accumulated model, strengthening operator model, weakening operator model and unequal interval model. And the theory and practical significance of the extended model is analyzed. [ABSTRACT FROM AUTHOR]

The precision of the laser gyro used in tactical missiles is poor because of dithering frequency, actuating by vibration, shock and overload in dynamical environment. This paper introduces the transfer matrix method of the multibody system (MSTMM), establishes the dynamic model of the laser gyro strapdown inertial measure assembly aseismatic system, and analyzes the precision affected by dithering of the laser gyro and shocking of the tactical missile. And the dynamic response of the laser gyro strapdown inertial measure assembly aseismatic system is obtained by simulating the multibody system model. The simulation result indicates a theoretical idea to design the vibration isolation for the laser gyro strapdown inertial measure assembly. [ABSTRACT FROM AUTHOR]