Iterative Learning Control With Incomplete Information： A Survey

Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.

Anti-JPEG Compression Steganography Based on the High Tense Region Locating Method

Robust data hiding techniques attempt to construct covert communication in a lossy public channel.Nowadays,the existing robust JPEG steganographic algorithms cannot overcome the side-information missing situation.Thus,this paper proposes a new robust JPEG steganographic algorithm based on the high tense region location method which needs no side-information of lossy channel.First,a tense region locating method is proposed based on the Harris-Laplacian feature point.Then,robust cover object generating processes are described.Last,the advanced embedding cost function is proposed.A series of experiments are conducted on various JPEG image sets and the results show that the proposed steganographic algorithm can resist JPEG compression efficiently with acceptable performance against steganalysis statistical detection libraries GFR(Gabor Filters Rich model)and DCTR(Discrete Cosine Transform Residual).

Robust lossless data hiding scheme

This paper presents a robust lossless data hiding scheme. The original cover image can be recovered without any distortion after data extraction if the stego-image remains intact, and conversely, the hidden data can still be extracted correctly if the stego-image goes through JPEG compression to some extent. A cover image is divided into a number of non-overlapping blocks, and the arithmetic difference of each block is calculated. By shifting the arithmetic difference value, we can embed bits into the blocks. The shift quantity and shifting rule are fixed for all blocks, and reversibility is achieved. Furthermore, because the bit-0- and bit-1-zones are separated and the particularity of the arithmetic differences, minor changes applied to the stego-image generated by non-malicious attacks such as JPEG compression will not cause the bit-0- and bit-l-zones to overlap, and robustness is achieved. The new embedding mechanism can enhance embedding capacity and the addition of a threshold can make the al- gorithm more robust. Experimental results showed that, compared with previous schemes, the performance of the proposed scheme is significantly improved.