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While the ATM-based broadband ISDN network gives the possibility for source coding at the variable-bit rate (VBR), it also benefits from the VBR coding. The advantages of VBR coding include consistent picture quality. bandwidth savings and delay reduction. However, one of the major drawbacks of ATM networks is the cell loss and consequent aggravated picture degradation in case of VBR coding. At the present time. there seems to be no effective method to completely prevent from the cell dropping. Many compensative measures have been proposed recently to make this objective cell loss subjectively imperceivable. These schemes include the simple ARQ scheme, error concealment by command refreshment I appropriate queuing discipline and priority switching design, layered source coding schemes and other signal processing techniques. This paper intends to summarize these efforts and, in particular, elaborate on different layered source coding schemes. Four types of signal priority classification schemes are identified: bitplane separation (BPS), frequency-domain separation (FDS), combined bitplane-frequency separation (CBFS) and feature plane separation (FPS). It is illustrated that the CBFS offers a good alternative to the FDS for possible cell dropping compensations in the ATM network.Different layered source coding schemes are described and compared, and a CBFS-based combined-transform coding (CTC) scheme is his hlig hied.

In this paper, a method to enhance the security of the optical stealth channel is proposed. The proposed method uses the techniques of polarization modulator based code-shift-keying (CSK) data modulation and optical code-division multiple-access (OCDMA) en/decoding, where an incoherent light source is needed. Our analysis and experimental results show that the CSK-OCDMA signal, where a wavelength selective switch is used for optical en/decoding, has been stealthily transmitted over a 40-km wavelength-division multiplexing optical fiber link. In addition, the stealth channel only causes a power penalty less than 0.48 dB to the public channel, whereas both of these two channels can achieve error-free transmission (with bit error rate less than 10 À9 ).Index Terms: Optical code-division multiple access (OCDMA), optical steganography, optical security and encryption, code-shift keying (CSK).

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Line loss is inherent in transmission and distribution stages, which can cause certain impacts on the profits of power-supply corporations. Thus, it is an important indicator and a benchmark value of which is needed to evaluate daily line loss rates in low voltage transformer regions. However, the number of regions is usually very large, and the dataset of line loss rates contains massive outliers. It is critical to develop a regression model with both great robustness and efficiency when trained on big data samples. In this case, a novel method based on robust neural network (RNN) is proposed. It is a multi-path network model with denoising auto-encoder (DAE), which takes the advantages of dropout, L2 regularization and Huber loss function. It can achieve several different outputs, which are utilized to compute benchmark values and reasonable intervals. Based on the comparison results, the proposed RNN possesses both superb robustness and accuracy, which outperforms the testing conventional regression models. According to the benchmark analysis, there are about 13% outliers in the collected dataset and about 45% regions that hold outliers within a month. Hence, the quality of line loss rate data should still be further improved.