We consider the minimum input selection problem for structural controllability (MISSC), stated as follows: Given a linear system ẋ = Ax, where A is a n × n state matrix with m nonzero entries, find the minimum number of states that need to be driven by an external input so that the resulting system is structurally controllable. The fastest algorithm to solve this problem was recently proposed b...

Extreme learning machine is a new learning algorithm for the single hidden layer feedforward neural networks (SLFNs). ELM has been widely used in various fields and applications to overcome the slow training speed and over-fitting problems of the conventional neural network learning algorithms. ELM algorithm is based on the empirical risk minimization, without considering the structural risk an...

In this paper necessary and sufficient conditions (and criteria) for null-controllability, reachability and controllability of time-variant discrete-time positive linear systems are established. These properties appear to be entirely structural properties, that is, they do depend on the zero-nonzero pattern of the pair (A(k), B(k)) ≥ 0 and do not depend on the values of its entries. An interest...

In testing systems with distributed interfaces/ports we may place a separate tester at each port. It is known that this approach can introduce controllability problems which have received much attention in testing from finite state machines. Message Sequence Charts (MSCs) form an alternative, commonly used, language for modelling distributed systems. However, controllability problems in testing...

This paper proposes the Gramian-preserving frequency transformation for linear discrete-time state-space systems. In this frequency transformation, we replace each delay element of a discrete-time system with an allpass system that has a balanced realization. This approach can generate transformed systems that have the same controllability/observability Gramians as those of the original system....