Abstract:Traditional Nakagami fading models can not provide satisfactory temporal correlation. Based on channel decomposition technique and sum-of-sinusoids (SOS) method, a novel complex Nakagami fading channel simulator was proposed. The new model allows for arbitrary fading parameter and prespecified temporal correlation. In this paper, we firstly derived the relationships between Rayleigh and Nakagami random process, and then presented a modified Nakagami envelope decomposition model by Rayleigh processes. Finally, arbitrary temporal correlated Nakagami fadings are generated combining with SOS method. Simulation results verify that the output channel of new model has more accurate autocorrelation coefficient than other models, and the statistical properties, such as envelope and phase distributions, are also very close to the theoretical results

Abstract:n the WSN - WIM system, the sensor fault diagnosis is a critical issue. This paper proposes a sensor fault diagnosis method based on the grey prediction theory, while the gray prediction model was optimized to avoid the theoretical defect of prediction model to the first sensor fault diagnosis caused by false assumptions. Over simulation experiment of WSN-WIM system , achieved an less than 0.3% average error,and 100% diagnostic accuracy. moreover this method has small computation, Good real-time performance, strong ability of self-adaptability, self-diagnostic and so on. It is very suitable for embedded, distributed high-speed dynamic multi-sensor weighing systems.

Abstract:A new sampled data processing method of switch antenna is proposed for space-time spectrum estimate in switch antenna array system. This method constructs the switch antenna array’s particular array manifold matrix and steering vector which contains channel switch interval and sampling interval. It dispenses with pretreatment to original data so that they can apply to the existing spectrum estimate algorithm directly. Based on this data processing method, distortionless space-time planar array algorithm and irredundant L-shaped array spectrum estimate algorithm in switch antenna array are given. With smaller hardware scale, the two algorithms which avoid signal distortion are more closed to multi-receiver array algorithm in performance; the latter one’s computational complexity is also lower through the comparison of algorithm cost among the classical algorithms and the proposed algorithms. Simulation analysis verifies that the two algorithms are effective.

Abstract:In view of some problems such as the complex calculating process, large deviation compared with ideal pink noise on the existing generation methods of pink noise, this paper puts forward a new generating method of pink noise using Auto-regressive moving average (ARMA) model; First, constructing an ARMA model of undetermined coefficients, and deriving the formula by Z transform and power spectrum estimation; Second, using the known pink noise analog filter transfer function H(s) and the principle of bilinear Z transformation method to derive IIR digital filter transfer function H(z), and then the ARMA model of pink noise can be obtained; Finally, using MATLAB to do its power spectrum estimation and comparing with the ideal pink noise. As the MATLAB simulation results shown, this method has a higher fitting degree with ideal pink noise and complies with the performance requirements of pink noise.

Abstract:We proposed a blind separation method based on second-order statistics for hopping-frequency signals. Firstly, a cost function was constructed to estimate separation matrix by exploiting the properties of non-stationary and non-whitening of signals, then updated the separation matrix by gradient steepest method, so as to obtain optimal separation matrix. The simulation results show that the method can separate multiple-hopping frequency signals off- or on-line, and its superior robustness performance to the conventional methods.

Abstract:Integer transform and quantization play very important role on the improving of encoding performance in H.264/AVC. As the motion estimation is improved, the portion of the transform and quantization becomes approximately 24% of the total computations. This cannot be neglected for the realization of the encoder. Therefore, it is meaningful to develop the efficient transform and quantization for fast encoding. An improved algorithm for the transform and quantization based on the early detection of all-zero blocks in H.264/AVC video encoding is proposed in this paper. According to the characteristic of 4*4 integer block , 4*4 luma DC coefficients and 2*2 chroma DC coefficients, all-zero blocks can be detected and integer transform and quantization are skipped for the all-zero blocks. The simulation results show that the proposed algorithm achieves approximately 21.29% computational saving with little video quality degradation, compared to the conventional method.

Abstract:To improve the state estimation accuracy for CIR term structure model of interest rates, this paper establishes the discrete nonlinear filtering formulation of CIR model and then adopts Gaussian particle filter (GPF) to generate the approximate optimal state estimation. Compared with the popular extended Kalman filter (EKF), GPF employs Gaussian distribution based on importance sampling algorithm to approximate the posterior probability while avoiding the error resulting from linearly approximating the function itself. The two nonlinear estimation methodologies are implemented and compared on simulated data. Results are presented to demonstrate the more accurate ability of GPF-based CIR filtering model to describe the dynamics of the term structure of interest rates.