When an autonomous robot is to learn its behavior, whether an appropriate state space is available or not is a most critical issue for the flexibility and efficiency of the learning process. What is problematic is that it is usually very difficult to prepare such an ideal state space manually beforehand. In this paper, we propose a new state space “reconstruction” method. With this, behavior-ba...

We establish necessary and sufficient conditions for consistent root reconstruction in continuous-time Markov models with countable state space on bounded-height trees. Here a root state estimator is said to be consistent if the probability that it returns to the true root state converges to 1 as the number of leaves tends to infinity. We also derive quantitative bounds on the error of reconstr...

Anterior cruciate ligament (ACL) reconstruction surgery has significantly evolved in recent years. This has led to development of new technologies that facilitate the diagnosis of ACL injury and the application of state of the art methods for treatment. In particular, individualized anatomical ACL reconstruction aims to restore native ACL function. Treatment is tailored to each patient based on...

This paper provides the theoretic foundation for the design of L optimal reconstructors (aka interpolators / holds) with a prescribed degree of causality. A compact frequency domain solution is derived which mimics known interpolation techniques for ordinary transfer functions. In parallel an extensive state space solution is documented. It complements the frequency domain solution in that it c...

This paper presents a new methodology for designing a detection, isolation, and identification scheme for sensor faults in linear timevarying systems. Practically important is that the proposed methodology is constructed on the basis of historical data and does not require a priori information to isolate and identify sensor faults. This is achieved by identifying a state space model and designi...

The analysis of chaotic time series requires proper reconstruction of the state space from the available data in order to successfully estimate invariant properties of the embedded attractor. Using the correlation dimension, we discuss the applicability of the two most common methods of reconstruction, the method of delays (MOD) and the Singular Spectrum Approach (SSA). Contrary to previous dis...