The aim of the paper is to develop comprehensive logical systems capable of handling both resource-sensitive and time-dependent properties of concurrent processes. As a language for specifying such properties, we introduce 'temporal linear logic' (TLL) an extension of linear logic with certain features of temporal logic. A semantic setting for TLL is given in terms of 'time-state universes'. TLL is proved to be fully adequate for 'time-state' concurrency models.

Statistical recognition procedures can be derived from the functional form of underlying probability distributions. Successive approximation to the probability function leads to a class of recognition procedures. In this note we give a hierarchical method of designing recognition functions which satisfy both the least-square error property and a minimum decision error rate property, although our discussions are restricted to a binary measurement space and its dichotomous classification.