Minimizing the effect of sinusoidal trends in detrended fluctuation analysis

The detrended fluctuation analysis (DFA) [Peng et al., 1994] and its extensions (MF-DFA) [Kantelhardt et al., 2002] have been used extensively to determine possible long-range correlations in self-affine signals. While the DFA has been claimed to be a superior technique, recent reports have indicated its susceptibility to trends in the data. In this report, a smoothing filter is proposed to minimize the effect of sinusoidal trends and distortion in the log-log plots obtained by DFA and MF-DFA techniques

Deep learning for interference cancellation in non-orthogonal signal based optical communication systems

Non-orthogonal waveforms are groups of signals, which improve spectral efficiency but at the cost of interference. A recognized waveform, termed spectrally efficient frequency division multiplexing (SEFDM), which was a technique initially proposed for wireless systems, has been extensively studied in 60 GHz millimeter wave communications, optical access network design and long haul optical fiber transmission. Experimental demonstrations have shown the advantages of SEFDM in its bandwidth saving, data rate improvement, power efficiency improvement and transmission distance extension compared to conventional orthogonal communication techniques. However, the achieved success of SEFDM is at the cost of complex signal processing for the mitigation of the self-created inter carrier interference (ICI). Thus, a low complexity interference cancellation approach is in urgent need. Recently, deep learning has been applied in optical communication systems to compensate for linear and non-linear distortions in orthogonal frequency division multiplexing (OFDM) signals. The multiple processing layers of deep neural networks (DNN) can simplify signal processing models and can efficiently solve un-deterministic problems. However, there are no reports on the use of deep learning to deal with interference in non-orthogonal signals. DNN can learn complex interference features using backpropagation mechanism. This work will present our investigations on the performance improvement of interference cancellation for the non-orthogonal signal using various deep neural networks. Simulation results show that the interference within SEFDM signals can be mitigated efficiently via using properly designed neural networks. It also indicates a high correlation between neural networks and signal waveforms. It verifies that in order to achieve the optimal performance, all the neurons at each layer have to be connected. Partially connected neural networks cannot learn complete interference and therefore cannot recover signals efficiently. This work paves the way for the research of simplifying neural networks design via signal waveform optimization

Slot error rate performance of DH-PIM with symbol retransmission for optical wireless links

In this paper we introduce the dual-header pulse interval modulation (DH-PIM) technique employing a simple retransmission coupled with a majority decision detection scheme at the receiver. We analytically investigate the slot error rate (SER) performance and compare results with simulated data for the symbol retransmissions rates of three, four and five, showing a good agreement. We demonstrate that the proposed scheme significantly reduces the SER compared with the standard single symbol transmission system, with retransmission rate of five offering the highest code gain of 5 dB

Reliable scaling exponent estimation of long-range correlated noise in the presence of random spikes

Detrended fluctuation analysis (DFA) has been used widely to determine possible long-range correlations in data obtained from diverse settings. In a recent study [1], uncorrelated random spikes superimposed on the long-range correlated noise (LR noise) were found to affect DFA scaling exponent estimates. In this brief communication, singular-value decomposition (SVD) filter is proposed to minimize the effect random spikes superimposed on LR noise, thus facilitating reliable estimation of the scaling exponents. The effectiveness of the proposed approach is demonstrated on random spikes sampled from normal and uniform distributions.Comment: 36 Pages, 20 Figure

On BER Performance of EBPSK-MODEM in AWGN Channel

In order to satisfy the higher and higher demand for communication systems, an Extended Binary Phase Shift Keying (EBPSK) system with very high spectra efficiency has been proposed. During the research, a special kind of filters was found, which can amplify the signal characteristics and remove utmost noise, i.e., at the point of the phase jumping corresponding to code “1”, produce the amplitude impulse much higher than code “0”, therefore, the aim of our study was to analyze the BER performance of the impacting filter assisted EBPSK-MODEM. Considering the receiver filtered “0” and “1”signal with Rice amplitude distribution, just having different mean values, so the BER performance of EBPSK is deduced based on the classic detection theory, and compared with the traditional BPSK modulation both in spectra efficiency and in BER performance, which lays the theoretical foundation for the feasibility of Ultra Narrow Band communications based on EBPSK modulation

Effect of coarse-graining on detrended fluctuation analysis

Several studies have investigated the scaling behavior in naturally occurring biological and physical processes using techniques such as detrended fluctuation analysis (DFA). Data acquisition is an inherent part of these studies and maps the continuous process into digital data. The resulting digital data is discretized in amplitude and time, and shall be referred to as coarse-grained realization in the present study. Since coarse-graining precedes scaling exponent analysis, it is important to understand its effects on scaling exponent estimators such as DFA. In this brief communication, k-means clustering is used to generate coarse-grained realizations of data sets with different correlation properties, namely: anti-correlated noise, long-range correlated noise and uncorrelated noise. It is shown that the coarse-graining can significantly affect the scaling exponent estimates. It is also shown that scaling exponent can be reliably estimated even at low levels of coarse-graining and the number of the clusters required varies across the data sets with different correlation properties.Comment: 21 Pages, 10 Figures. Physica A, 2005 (in press

Is a multiple excitation of a single atom equivalent to a single excitation of an ensemble of atoms?

Recent technological advances have enabled to isolate, control and measure the properties of a single atom, leading to the possibility to perform statistics on the behavior of single quantum systems. These experiments have enabled to check a question which was out of reach previously: Is the statistics of a repeatedly excitation of an atom N times equivalent to a single excitation of an ensemble of N atoms? We present a new method to analyze quantum measurements which leads to the postulation that the answer is most probably no. We discuss the merits of the analysis and its conclusion.Comment: 3 pages, 3 figure

Quantum storage on subradiant states in an extended atomic ensemble

A scheme for coherent manipulation of collective atomic states is developed such that total subradiant states, in which spontaneous emission is suppressed into all directions due to destructive interference between neighbor atoms, can be created in an extended atomic ensemble. The optimal conditions for creation of such states and suitability of them for quantum storage are discussed. It is shown that in order to achieve the maximum signal-to-noise ratio the shape of a light pulse to be stored and reconstructed using a homogeneously broadened absorbtion line of an atomic system should be a time-reversed regular part of the response function of the system. In the limit of high optical density, such pulses allow one to prepare collective subradiant atomic states with near flat spatial distribution of the atomic excitation in the medium.Comment: V2: considerably revised (title, text). V3: minor changes - final version as published in PR

Feasibility study of non-invasive telemetry techniques for use with submarine telephone cables

The feasibility of using inductive coupling with existing submarine telephone cables for telemetry of data from ocean sensors was investigated. The submarine telephone cable was simulated with a computer model and the model results were tested experimentally by deploying 600 meters of coax cable in Woods Hole Harbor. In parallel a study of the optimum access methods and modulation and techniques was performed. Results of the feasibility study showed that a non-invasive technique for inductive coupling is not feasible for use with existing SF and SD coaxial cable designs. Signals induced in both conductors by a toroid encircling the cable remain identical as they propagate along the cable as a result of mutual inductance. Thus, no signals are apparent at the repeaters. Optimal use of cable bandwidth combines time division multiple access with trellis-coded QAM modulation.Funding was provided by the IRIS Consortium under sub-award agreement No. 0169 and by the W.M. Keck Foundation through their Technology Innovation Awards