6839976
Iterative Filtering as an Alternative Algorithm for Empirical Mode Decomposition
The empirical mode decomposition (EMD) was a method pioneered by (N. Huang et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear nonstationary time series analysis, Proc. Roy. Soc. Lond. A454 (1998) 903–995) as an alternative technique to the traditional Fourier and wavelet techniques for studying signals. It decomposes a signal into several components called intrinsic mode functions (IMFs), which have shown to admit better behaved instantaneous frequencies via Hilbert transforms. In this paper, we propose an alternative algorithm for EMD based on iterating certain filters, such as Toeplitz filters. This approach yields similar results as the more traditional sifting algorithm for EMD. In many cases the convergence can be rigorously proved.
17540624
Asymptotic White noise Hypothesis for PCM quantization
For a signal distributed in Rd with an arbitrary density we find the limit distribution as the cell size goes to zero of the quantization noise in the case of a redundant system and the pulse-code modulation scheme. The dimension the support of the limiting distribution equals the largest number of non-comeasurable vectors in the frame and the limit distribution is uniform over its support. This gives the necessary and sufficient conditions for the asymptotic form of the white noise hypothesis.
14757772
Convergence of a Convolution-Filtering-Based Algorithm for Empirical Mode Decomposition
Lin et al. propose the iterative Toeplitz filters algorithm as an alternative iterative algorithm for Empirical Mode Decomposition (EMD). In this alternative algorithm, the average of the upper and lower envelopes is replaced by certain "moving average" obtained through a low-pass filter. Performing the traditional sifting algorithm with such moving averages is equivalent to iterating certain convolution filters (finite length Toeplitz filters). This paper studies the convergence of this algorithm for signals of continuous variables, and proves that the limit function of this iterative algorithm is an ideal high-pass filtering process.
9587091
Topology control for delay-constraint data collection in wireless sensor networks
Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.
37274241
Preparation of one-dimensional photonic crystal with variable period by using ultra-high vacuum electron beam evaporation
One-dimensional photonic crystal with variable period has been prepared by using the method of ultra-high vacuum electron beam evaporation. Advantage of this method is gaining variable period easily. The transmittance of the photonic crystal has been also studied.
33302534
A space-efficient algorithm for sequence alignment with inversions and reversals
A dynamic programming algorithm to find an optimal alignment for a pair of DNA sequences has been described by Schoniger and Waterman. The alignments use not only substitutions, insertions, and deletions of single nucleotides, but also inversions, which are the reversed complements, of substrings of the sequences. With the restriction that the inversions are pairwise non-intersecting, their proposed algorithm runs in O(n2m2) time and consumes O(n2m2) space, where n and m are the lengths of the input sequences, respectively. We develop a space-efficient algorithm to compute such an optimal alignment which consumes only O(nm) space within the same amount of time. Our algorithm enables the computation for a pair of DNA sequences of length up to 10,000 to be carried out on an ordinary desktop computer. Simulation study is conducted to verify some biological facts about gene shuffling across species.
17669846
Research on the Robustness of a Proportional Integral Switching Surface Based on Sliding Mode Control
In this paper, a novel proportional-integral (PI) switching surface is introduced for determining the synchronization performance of systems in the sliding mode motion. Based on the sliding mode controller, the system is established by a robust control scheme which guarantees the occurrence of a sliding motion of error states even when the parameter uncertainty and external disturbance are present. So this paper researches on robust synchronization problem by investigating a highly complex dynamic nonlinear system—chaotic systems. Some simulation results on controlling different chaotic systems are made and investigated in order to demonstrate the good performance of the method and this control design process is much easier to be completed.
12687767
Comments on "Estimation of frequencies and damping factors by two-dimensional ESPRIT type methods"
For original paper, see Rouquette and Najim (IEEE Trans. Signal Process., vol.49, no.1, p.237-45, 2001).The original authors present two high-resolution approaches to estimate two-dimensional (2-D) signal parameters. The first approach decomposes the 2-D estimation problem into two one-dimensional (1-D) ones, estimates the 1-D frequencies with the MEMP method, and then forms correct pairs using a new pairing scheme introduced in Vanpoucke et al. (1994). The second method (the 2-D ESPRIT method) directly estimates the 2-D frequencies. It is shown that both methods are more accurate than the related methods. The present authors note that the original paper appears to have a key error in the permutation matrix specification of the first method. In this comment, they derive the correct one with the performance simulations.