Abstract:
In this paper, we consider the problem of variable-length source coding allowing errors. The exponential moment of the codeword length is analyzed in the non-asymptotic regime and in the asymptotic regime. Our results show that the smooth Renyi entropy characterizes the optimal exponential moment of the codeword length.

Abstract:
An efficient chaotic source coding scheme operating on variable-length blocks is proposed. With the source message represented by a trajectory in the state space of a chaotic system, data compression is achieved when the dynamical system is adapted to the probability distribution of the source symbols. For infinite-precision computation, the theoretical compression performance of this chaotic coding approach attains that of optimal entropy coding. In finite-precision implementation, it can be realized by encoding variable-length blocks using a piecewise linear chaotic map within the precision of register length. In the decoding process, the bit shift in the register can track the synchronization of the initial value and the corresponding block. Therefore, all the variable-length blocks are decoded correctly. Simulation results show that the proposed scheme performs well with high efficiency and minor compression loss when compared with traditional entropy coding.

Abstract:
Using invariance of the $n$-th tensored state w.r.t. the $n$-th symmetric group, we propose a 'variable length' universal entanglement concentration without classical communication. Like variable length data compression, arbitrary unknown states are concentrated into perfect Bell states and not approximate Bell states and the number of Bell states obtained is equal to the optimal rate asymptotically with the probability 1. One of the point of our scheme is that we need no classical communication at all. Using this method, we can construct a universal teleportation and a universal dense coding.

Abstract:
This paper studies variable-length (VL) source coding of general sources with side-information. Novel one-shot coding theorems for coding with common side-information available at the encoder and the decoder and Slepian- Wolf (SW) coding (i.e., with side-information only at the decoder) are given, and then, are applied to asymptotic analyses of these coding problems. Especially, a general formula for the infimum of the coding rate asymptotically achievable by weak VL-SW coding (i.e., VL-SW coding with vanishing error probability) is derived. Further, the general formula is applied to investigating weak VL-SW coding of mixed sources. Our results derive and extend several known results on SW coding and weak VL coding, e.g., the optimal achievable rate of VL-SW coding for mixture of i.i.d. sources is given for countably infinite alphabet case with mild condition. In addition, the usefulness of the encoder side-information is investigated. Our result shows that if the encoder side-information is useless in weak VL coding then it is also useless even in the case where the error probability may be positive asymptotically.

Abstract:
Universal fixed-to-variable lossless source coding for memoryless sources is studied in the finite blocklength and higher-order asymptotics regimes. Optimal third-order coding rates are derived for general fixed-to-variable codes and for prefix codes. It is shown that the non-prefix Type Size code, in which codeword lengths are chosen in ascending order of type class size, achieves the optimal third-order rate and outperforms classical Two-Stage codes. Converse results are proved making use of a result on the distribution of the empirical entropy and Laplace's approximation. Finally, the fixed-to-variable coding problem without a prefix constraint is shown to be essentially the same as the universal guessing problem.

Abstract:
This paper deals with a universal coding problem for a certain kind of multiterminal source coding network called a generalized complementary delivery network. In this network, messages from multiple correlated sources are jointly encoded, and each decoder has access to some of the messages to enable it to reproduce the other messages. Both fixed-to-fixed length and fixed-to-variable length lossless coding schemes are considered. Explicit constructions of universal codes and the bounds of the error probabilities are clarified by using methods of types and graph-theoretical analysis.

Abstract:
This paper deals with a universal coding problem for a certain kind of multiterminal source coding system that we call the complementary delivery coding system. In this system, messages from two correlated sources are jointly encoded, and each decoder has access to one of the two messages to enable it to reproduce the other message. Both fixed-to-fixed length and fixed-to-variable length lossless coding schemes are considered. Explicit constructions of universal codes and bounds of the error probabilities are clarified via type-theoretical and graph-theoretical analyses. [[Keywords]] multiterminal source coding, complementary delivery, universal coding, types of sequences, bipartite graphs

Abstract:
Second order asymptotics of fixed-length source coding and intrinsic randomness is discussed with a constant error constraint. There was a difference between optimal rates of fixed-length source coding and intrinsic randomness, which never occurred in the first order asymptotics. In addition, the relation between uniform distribution and compressed data is discussed based on this fact. These results are valid for general information sources as well as independent and identical distributions. A universal code attaining the second order optimal rate is also constructed.

Abstract:
We derive the optimal exponent of the error probability of the quantum fixed-length pure state source coding in both cases of blind coding and visible coding. The optimal exponent is universally attained by Jozsa et al. (PRL, 81, 1714 (1998))'s universal code. In the direct part, a group representation theoretical type method is essential. In the converse part, Nielsen and Kempe (PRL, 86, 5184 (2001))'s lemma is essential.

Abstract:
The problem of the universal compression of a sequence from a library of several small to moderate length sequences from similar context arises in many practical scenarios, such as the compression of the storage data and the Internet traffic. In such scenarios, it is often required to compress and decompress every sequence individually. However, the universal compression of the individual sequences suffers from significant redundancy overhead. In this paper, we aim at answering whether or not having a memory unit in the middle can result in a fundamental gain in the universal compression. We present the problem setup in the most basic scenario consisting of a server node $S$, a relay node $R$ (i.e., the memory unit), and a client node $C$. We assume that server $S$ wishes to send the sequence $x^n$ to the client $C$ who has never had any prior communication with the server, and hence, is not capable of memorization of the source context. However, $R$ has previously communicated with $S$ to forward previous sequences from $S$ to the clients other than $C$, and thus, $R$ has memorized a context $y^m$ shared with $S$. Note that if the relay node was absent the source could possibly apply universal compression to $x^n$ and transmit to $C$ whereas the presence of memorized context at $R$ can possibly reduce the communication overhead in $S$-$R$ link. In this paper, we investigate the fundamental gain of the context memorization in the memory-assisted universal compression of the sequence $x^n$ over conventional universal source coding by providing a lower bound on the gain of memory-assisted source coding.