This paper clarifies a necessary condition and a sufficient condition for transmissibility for a given set of general sources and a given general broadcast channel. The approach is based on the information-spectrum methods introduced by Han and Verdu. Moreover, we consider the capacity region of the general broadcast channel with arbitrarily fixed error probabilities if we send independent private and common messages over the channel. Furthermore, we treat the capacity region for mixed broadcast channel.

In this letter, we first introduce a stronger notion of the optimistic achievable coding rate and discuss a coding theorem. Next, we give a necessary and sufficient condition under which the coding rates of all the optimal FF codes asymptotically converge to a constant.

A generalization of compression via substring enumeration (CSE) for k-th order Markov sources with a finite alphabet is proposed, and an upper bound of the codeword length of the proposed method is presented. We analyze the worst case maximum redundancy of CSE for k-th order Markov sources with a finite alphabet. The compression ratio of the proposed method asymptotically converges to the optimal one for k-th order Markov sources with a finite alphabet if the length n of a source string tends to infinity.

This paper describes an efficient and simple coding algorithm of universally optimal codes for stationary (ergodic) sources and noiseless channel with unequal symbol costs. The symbol cost indicates the required time (or space) for the transmission (or storage) of that symbol, and the cost of any code symbol depends only on that symbol. The proposed coding algorithm mainly consists of two parts. The first part is based on the well-known Ziv-Lempel coding algorighm proposed in 1978 (sometimes called LZ78), and the second part is based on the Varn coding algorithm. The coding algorithm asymptotically achieves an optimal average cost of codes for stationary sources, and also achieves an optimal cost of codes for stationary ergodic sources with probability one. Furthermore, the computational complexity of the proposed coding algorithm is linear with respect to the length of source sequence and coded sequence.

The minimization problem of an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints is formulated for a class of two-dimensional (2-D) state-space digital filters. First, the problem is converted into an unconstrained optimization problem by using linear-algebraic techniques. Next, the unconstrained optimization problem is solved by applying an efficient quasi-Newton algorithm with closed-form formula for gradient evaluation. The coordinate transformation matrix obtained is then used to synthesize the optimal 2-D state-space filter structure that minimizes the L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints. Finally, a numerical example is presented to illustrate the utility of the proposed technique.

Recently, Muramatsu proposed source coding algorithms that use the randomness of a past sequence. The technique of his source coding algorithms is one method of constructing codes from the technique of random coding. By using his technique, we propose a channel coding algorithm with random numbers which can be observed by both the encoder and the decoder where the random numbers are independent of the messages to be transmitted. Then the proposed coding algorithm can transmit messages over a discrete memoryless channel up to the channel capacity with an arbitrarily small decoding error rate and arbitrarily small bits of random numbers per message transmission asymptotically.

Many Ziv-Lempel algorithms have a similar property, that is, slow encoding and fast decoding. This paper proposes a simple improved Ziv-Lempel algorithm to encode a large amount of data quickly as well as compactly by using multiple-processor system.

Wyner and Ziv considered the rate-distortion function for source coding with side information at the decoder (we call the Wyner-Ziv problem). In this paper we show an information-spectrum approach to the Wyner-Ziv problem for general class of nonstationary and/or nonergodic sources with side information at the decoder, where the distortion measure is arbitrary and may be nonadditive. We show that a general formula for the rate-distortion function of the Wyner-Ziv problem for general sources with the maximum distortion criterion under fixed-length coding by using the information spectrum approach.

Dubé and Beaudoin proposed a lossless data compression called compression via substring enumeration (CSE) in 2010. We evaluate an upper bound of the number of bits used by the CSE technique to encode any binary string from an unknown member of a known class of k-th order Markov processes. We compare the worst case maximum redundancy obtained by the CSE technique for any binary string with the least possible value of the worst case maximum redundancy obtained by the best fixed-to-variable length code that satisfies the Kraft inequality.

In this paper we consider fixed-to-fixed length (FF) coding of a general source X with vanishing error probability and define two kinds of optimalities with respect to the coding rate and the redundancy, where the redundancy is defined as the difference between the coding rate and the symbolwise ideal codeword length. We first show that the infimum achievable redundancy coincides with the asymptotic width W(X) of the entropy spectrum. Next, we consider the two sets $mCH(X)$ and $mCW(X)$ and investigate relationships between them, where $mCH(X)$ and $mCW(X)$ denote the sets of all the optimal FF codes with respect to the coding rate and the redundancy, respectively. We give two necessary and sufficient conditions corresponding to $mCH(X) subseteq mCW(X)$ and $mCW(X) subseteq mCH(X)$, respectively. We can also show the existence of an FF code that is optimal with respect to both the redundancy and the coding rate.

In this paper, Information-Spectrum characterization is derived for the reliable transmission of general correlated sources over the general multiple-access channels. We consider the necessary and sufficient conditions for the transmission of general correlated sources over the general multiple-access channels by using Information-Spectrum methods which are introduced by Han and Verdu.

The class of k-bit delay decodable codes, source codes allowing decoding delay of at most k bits for k≥0, can attain a shorter average codeword length than Huffman codes. This paper discusses the general properties of the class of k-bit delay decodable codes with a finite number of code tables and proves two theorems which enable us to limit the scope of codes to be considered when discussing optimal k-bit delay decodable codes.