This letter deals with the common randomness problem formulated by Ahlswede and Csiszar. Especially, we consider their source-type models without wiretapper for ergodic sources, and clarify the secret key-capacity by using the bin coding technique proposed by Cover.

The digital filter which is constructed by Lebesgue spectrum analysis of ergodic theory, is shown to achieve a 15% gain of the number of simultaneous accessible users of asynchronous CDMA communication systems at the same BER (Bite Error Rate) compared to the Gold sequence and random sequence. According to the simulation of asynchronous CDMA communication systems with spreading sequences at the spreading factor of 127, it is shown that the performance gain caused by the digital filter called Lebesgue spectrum filter (LSF) is independent on the nature of spreading sequences.

Currently, the most popular model in data compression theory is that of stationary ergodic sources. But there do exist sequences each of which is not emitted from any stationary ergodic source but can be compressed sufficiently by a certain algorithm. We estimate the size of the set of such sequences in terms of Hausdorff dimension.

In this paper the performance of the Block Sorting algorithm proposed by Burrows and Wheeler is evaluated theoretically. It is proved that the Block Sorting algorithm is asymptotically optimal for stationary ergodic finite order Markov sources. Our proof is based on the facts that symbols with the same Markov state (or context) in an original data sequence are grouped together in the output sequence obtained by Burrows-Wheeler transform, and the codeword length of each group can be bounded by a function described with the frequencies of symbols included in the group.

Let {Xk}k=- be a stationary and ergodic information source, where each Xk takes values in a standard alphabet A with a distance function d: A A [0, ) defined on it. For each sample sequence X = (, x-1, x0, x1, ) and D > 0 let the approximate D-match recurrence time be defined by Rn (x, D) = min {m n: dn (Xn1, Xm+nm+1) D}, where Xji denotes the string xixi+1 xj and dn: An An [0, ) is a metric of An induced by d for each n. Let R (D) be the rate distortion function of the source {Xk}k=- relative to the fidelity criterion {dn}. Then it is shown that lim supn-1/n log Rn (X, D) R (D/2) a. s.

This paper proposes an unsupervised speaker adaptation method using an all-phoneme ergodic Hidden Markov Network" that combines allophonic (context-dependent phone) acoustic models with stochastic language constraints. Hidden Markov Network (HMnet) for allophone modeling and allophonic bigram probabilities derived from a large text database are combined to yield a single large ergodic HMM which represents arbitrary speech signals in a particular language so that the model parameters can be re-estimated using text-unknown speech samples with the Baum-Welch algorithm. When combined with the Vector Field Smoothing (VFS) technique, unsupervised speaker adaptation can be effectively performed. This method experimentally gave better performances compared with our previous unsupervised adaptation method which used conventional phonetic HMMs and phoneme bigram probabilities especially when the amount of training data was small.

Binary sequences with good correlation properties are required for a variety of engineering applications. We previously proposed simple methods to generate binary sequences based on chaotic nonlinear maps. In this paper, statistical properties of chaotic binary sequences generated by Chebyshev maps are discussed. We explicitly evaluate the correlation functions by means of the ensemble–average technique based on the Perron–Frobenius (P–F) operator. As a consequence, we can confirm an important role of the P–F operator in evaluating statistics of chaos by means of the ensemble-average technique.

A simple method is given for obtaining new families of pseudonoise (PN) sequences based on chaotic non-linear maps. Such families are worse than the Gold and the Kasami families in terms of maximum correlation values. Nevertheless, such a method has several advantages: the generation is easy, and various families with an arbitrary family size and sequence period can be obtained primarily because non-linear maps have several parameters to be secret keys for communications security. Hence these sequences are good candidates of spreading sequences for CDMA.

A group-based random access communication system which consists of two groups of many users is considered. The two different groups share a common random multiple access channel. Users from a group are allocated a high transmitting power level and have a high probability of correct reception among overlapping packets. We set a threshold, θ, which is such that the group with the high power level will occupy the channel if less than or equal to θ packets are transmitted from the group with the low power level. We obtain a two-dimensional Markovian model by tracing the number of backlogged users in the two groups. The two-dimensional Markov chain is shown to be not ergodic and thus the system is not stable. A two-dimensional retransmission algorithm is developed to stabilize the system and the retransmission control parameters are chosen so as to maximize the channel throughput. An equilibrium point analysis is performed by studying the drift functions of the system backlog and it is shown that there is a unique global equilibrium point. The channel capacity for the system is found to be in the range from 0.47 up to 0.53, which is a remarkable increase compared to the conventional slotted ALOHA system.