Tunstall code is known as an optimal variable-to-fixed length (VF) lossless source code under the criterion of average coding rate, which is defined as the codeword length divided by the average phrase length. In this paper we define the average coding rate of a VF code as the expectation of the pointwise coding rate defined by the codeword length divided by the phrase length. We call this type of average coding rate the average pointwise coding rate. In this paper, a new VF code is proposed. An incremental parsing tree construction algorithm like the one that builds Tunstall parsing tree is presented. It is proved that this code is optimal under the criterion of the average pointwise coding rate, and that the average pointwise coding rate of this code converges asymptotically to the entropy of the stationary memoryless source emitting the data to be encoded. Moreover, it is proved that the proposed code attains better worst-case coding rate than Tunstall code.

Average coding rate of a multi-shot Tunstall code, which is a variation of variable-to-fixed length (VF) lossless source codes, for stationary memoryless sources is investigated. A multi-shot VF code parses a given source sequence to variable-length blocks and encodes them to fixed-length codewords. If we consider the situation that the parsing count is fixed, overall multi-shot VF code can be treated as a one-shot VF code. For this setting of Tunstall code, the compression performance is evaluated using two criterions. The first one is the average coding rate which is defined as the codeword length divided by the average block length. The second one is the expectation of the pointwise coding rate. It is proved that both of the above average coding rate converge to the entropy of a stationary memoryless source under the assumption that the geometric mean of the leaf counts of the multi-shot Tunstall parsing trees goes to infinity.

Almost sure convergence coding theorems of one-shot and multi-shot Tunstall codes are proved for stationary memoryless sources. Coding theorem of one-shot Tunstall code is proved in the case that the leaf count of Tunstall tree increases. On the other hand, coding theorem is proved for multi-shot Tunstall code with increasing parsing count, under the assumption that the Tunstall tree grows as the parsing proceeds. In this result, it is clarified that the theorem for the one-shot Tunstall code is not a corollary of the theorem for the multi-shot Tunstall code. In the case of the multi-shot Tunstall code, it can be regarded that the coding theorem is proved for the sequential algorithm such that parsing and coding are processed repeatedly. Cartesian concatenation of trees and geometric mean of the leaf counts of trees are newly introduced, which play crucial roles in the analyses of multi-shot Tunstall code.

The coding rate of a one-shot Tunstall code for stationary and memoryless sources is investigated in non-universal situations so that the probability distribution of the source is known to the encoder and the decoder. When studying the variable-to-fixed length code, the average coding rate has been defined as (i) the codeword length divided by the average block length. We define the average coding rate as (ii) the expectation of the pointwise coding rate, and prove that (ii) converges to the same value as (i).

The addition chain (A-chain) and addition-subtraction chain (AS-chain) are efficient tools to calculate power Me (or multiplication eM), where integere is fixed andM is variable. Since the optimization problem to find the shortest A (or AS)-chain is NP-hard, many algorithms to get a sub-optimal A (or AS)-chain in polynomial time are proposed. In this paper, a window method for the AS-chain and an extended window method for the A-chain and AS-chain are proposed and their performances are theoretically evaluated by applying the theory of the optimal variable-to-fixed length code, i. e. , Tunstall code, in data compression. It is shown by theory and simulation that the proposed algorithms are more efficient than other algorithms in practical cases in addition to the asymptotic case.