这篇文章介绍了一种基于Liquid State Machine (LSM)模型的时间序列预测方法。 LSM是一种脉冲神经网络,特别适用于处理时变或动态数据。

Finite State Machines (FSMs) serve as a foundational model for representing the behaviour of systems that transition between discrete states in response to inputs. Their applicability ranges from ...

This paper presents the Physhun project, a Spring-based framework for implementing complex processes through Finite State Machine models. Physhun provides finite State Model persistence and ...

The problem of machine translation can be viewed as consisting of two subproblems (a) lexical selection and (b) lexical reordering. In this paper, we propose stochastic finite-state models for these ...

IAR Systems’ Visual State, which works on Linux and Windows, simplifies the task of creating state-machine models.

Understanding the intricacies of NFA to DFA conversion provides a solid foundation for applying state machine thinking to system design.