**Research Interests (To be updated)**

**Prof. Yang's research interests broadly lie in the areas of information theory, digital signal processing, multimedia communications including multimedia compression, watermarking, and transmission with emphasis on information theoretic development, algorithm design and analysis, and applications. Recent topics of interest include without limitation:**

**Image Management(To be uptaded)**

**Multimedia data compression(To be uptaded)**

**A key technology driving force for multimedia communications is multimedia compression, which includes compression of text, audio, video and pictures. Depending on applications, compression can be lossless or lossy. Text compression such as Winzip compression is lossless. On the other hand, lossy compression such as MP3, JPEG, JPEG-2000, MPEG coding series, and H.26x series is popular for compressing rich media. Lossy compression is achieved by discarding information without severely affecting the user's perception of the media. A trade-off is created between quality and compression. In this research, we are interested in developing new theories for lossless and lossy compression and new efficient lossless and lossy compression algorithms, which may or may not be compatible with existing compression standards. Some of our prior works include grammar-based coding theory****[J15]****, grammar-based coding algorithms, fixed slope universal lossy coding****[J17]****, the philosophy of designing universal lossy coding algorithms from existing lossless algorithms, and optimization of JPEG, MP3, AAC, GIF/PNG, MPEG 2, and H.264.**

**Information and digital communications theory **

**Digital watermarking and information hiding **

**Transcoding for mobile communications and IPTV**

**As the variety of networks and types of client devices rapidly increase, transcoding, which studies how to convert multimedia data from one representation format to another format efficiently for delivering the content among heterogeneous platforms, has attracted wide attentions. The conversion may take place within the same standard scheme but with different configurations, e.g., CIF in H.264 to QCIF in H.264, or from one standard format to another standard format, e.g., from DV which is meant for high definition video to H.264 which as the newest standard supports a wide range of applications from video-on-demand to mobile video. In this work, we target image/video transcoding between mobile stations and mobile handsets, and video transcoding over IP networks, to build up a bridge for seamless interaction between multimedia production and consumption. **

**Mobile and wireless communications **

**TCP/IP, UDP, and multimedia streaming**

**Quantum information theory **

**Classical information theory can be roughly defined as a collection of coding theorems and is concerned (among other things) with data storage and transmission, where data processing devices are implicitly assumed to work according to the laws of classical physics and - so to speak - classical logic. Despite recent advances in hardware technology and exponentially growing computing power, conventional approaches to the fabrication of such electronic devices are beginning to run up against fundamental difficulties of size. As the size of the devices becomes smaller and smaller, they begin to function according to the laws of quantum mechanics, instead of the law of classical physics. Thus, the functioning of the super-small data processing devices can no longer be described and analyzed by means of classical information theory and one has to move to a different information-theoretic paradigm. This paradigm is based on the idea that information storage, processing, and transmission are governed by the laws of quantum logic and quantum mechanics, instead of classical ones. As quantum mechanics is the generalization of classical physics, quantum information theory****[J39]**** is the generalization of classical information theory. Thus, for example, quantum data compression, quantum cryptography, and quantum error correction are natural extensions of their classical counterparts, with classical information sources and classical messages being just special cases of quantum ones. Moreover, efficient classical codes are often utilized in the design of efficient quantum codes.**

**Kolmogorov complexity theory**

**Distributed source coding**