295 research outputs found

    Comment on: Stochastic local operations and classical communication Invariant and the residual entanglement for n qubits

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    In a recent paper [Phys. Rev. A 76, 032304(2007)], Li et al. proposed the definition of the residual entanglement for n qubits by means of the Stochastic local operations and classical communication. Here we argue that their definition is not suitable for the case of odd-n qubits.Comment: 3 pages, submitted to PR

    Beyond point forecasting: evaluation of alternative prediction intervals for tourist arrivals

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    This paper evaluates the performance of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models, innovations state-space models for exponential smoothing, and Harvey's structural time series models. We use thirteen monthly time series for the number of tourist arrivals to Hong Kong and to Australia. The mean coverage rate and length of alternative prediction intervals are evaluated in an empirical setting. It is found that the prediction intervals from all models show satisfactory performance, except for those from the autoregressive model. In particular, those based on the bias-corrected bootstrap in general perform best, providing tight intervals with accurate coverage rates, especially when the forecast horizon is long.Automatic forecasting, Bootstrapping, Interval forecasting

    Industrial agglomeration, spatial-temporal evolution and its driving factors: spatial interaction in Chinese leather industry

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    Taking the golden 20 years of the Chinese leather industry as an example, this paper adopts a spatial panel model to accurately portray the characteristics of spatial evolution and the trend of development of agglomeration of the leather industry. This paper further systematically identifies the key driving factors of leather industry agglomeration, taking into account the time effect, spatial effect, and spatio-temporal effect at the same time. The results show that China’s leather industry shows a shift from coastal areas to diffusion to inland areas. In terms of influencing factors, resource endowment and economic externality are the key force leading the agglomeration of leather industry. In addition, according to the results of group regression, it is found that innovation capacity and environmental regulation have become the main driving forces affecting the development of leather industry. Therefore, the government should carry out global planning according to the spatial pattern and transfer path of leather industry agglomeration. Based on the deep-level driving mechanism of industrial pattern evolution, specific industrial measures should be formulate to realize the development and promotion of leather industry in the new era

    To Achieve Security and High Spectrum Efficiency: A New Transmission System Based on Faster-than-Nyquist and Deep Learning

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    With the rapid development of various services in wireless communications, spectrum resource has become increasingly valuable. Faster-than-Nyquist (FTN) signaling, which was proposed in the 1970s, has been a promising paradigm to improve the spectrum utilization. In this paper, we try to apply FTN into secure communications and propose a secure and high-spectrum-efficiency transmission system based on FTN and deep learning (DL). In the proposed system, the hopping symbol packing ratio with random values makes it difficult for the eavesdropper to obtain the accurate symbol rate and inter-symbol interference (ISI). While the receiver can use the blind estimation to choose the true parameters with the aid of DL. The results show that without the accurate symbol packing ratio, the eavesdropper will suffer from severe performance degradation. As a result, the system can achieve a secure transmission with a higher spectrum efficiency. Also, we propose a simplified symbol packing ratio estimation which has bee employed in our proposed system. Results show that the proposed simplified estimation achieves nearly the same performance as the original structure while its complexity has been greatly reduced

    Application of Smart Antenna in TD - SCDMA

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    With the rapid development of global communications business, future personal communication wireless mobile communicationtechnology has aroused great concern. Way to eliminate the impact of co-channel interference (CCI), multiple access interference (MAI)and multipath fading becomes a major factor in improving the performance of wireless mobile communication systems. The smart antennauses the digital signal processing technology to generate the spatial directional beam so that the antenna main beam is aligned with thedirection of arrival of the user signal. The side lobe or the zero point is aligned to the direction of the interfering signal to reach the fullefficient use of the mobile subscriber signal, thus remove or suppress the interference signal purpose. Compared with other increasinglydeep and mature interference removal technology, the application of smart antenna technology in mobile communication is even more in theascendant and showing great potential. One of the key technologies of the third generation mobile communication standard TD-SCDMAsystem submitted by our country is the intelligent antenna technology. The paper introduces the history and development of the smartantenna in detail, and deeply analyzes the application of the smart antenna in TD-SCDMA. The application of smart antenna has beendeveloped