Abstract: A method for scheduling transmission of cells through a data switch having a plurality of inputs and outputs provides a plurality of buffers at each input. Each buffer corresponds to an output, or to a virtual circuit. A weight is assigned to each buffer; and buffers are selected according to a maximal weighted matching. Finally, cells are transmitted from the selected buffers to the corresponding outputs. Weights are based on number of credits associated with each buffer. Optionally, the weight is zero if the associated buffer is empty. A credit bucket size may be assigned to each buffer to limit the number of credits when the buffer is empty. Alternatively, weights are set to either buffer length, or to the number of credits, whichever is less. Or, weights may be set to validated waiting times associated with the oldest cells. Each input/output pair is assigned the maximum weight of any associated virtual connection.

Abstract: An image decoding and recognition system and method comprising a fast heuristic algorithm using hidden Markov models (HMM). The new search algorithm, called an "iterative complete path" (ICP) algorithm, patterned after well-known branch-and-bound (B&B) methods, significantly reduces the complexity and improves the speed of HMM image decoding without sacrificing the optimality of the straightforward procedure. An advantageous form of the heuristic functions which is useful in applying the ICP algorithm to text-like images is described. The ICP algorithm is directly applicable to the separable type of finite-state source models. Also disclosed is a technique for transforming more general source models into such a separable form.