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1 Introduction

— There is experimental evidence that a recently proposed subspace algorithm based on predictor identification has a behavior which is very close to prediction error methods in certain simple examples; this observation raises a question concerning its optimality. It is known that time series identification using the Canonical Correlation Analysis (CCA)… (More)

Subspace identification for closed loop systems has been recently studied by several authors. A class of new and consistent closed-loop subspace algorithms is based on identification of a predictor model, in a way similar as prediction error methods (PEM) do. Experimental evidence suggests that these methods have a behavior which is very close to PEM in… (More)

The causal estimation of three-dimensional motion from a sequence of two-dimensional images can be posed as a nonlinear filtering problem. We describe the implementation of an algorithm whose uniform observability, minimal realization and stability have been proven analytically in [5]. We discuss a scheme for handling occlusions, drift in the scale factor… (More)

- Re Vidal, Alessandro Chiuso
- 2000

%e analyze the observability of the continuous and discrete states of a class of linear hybrid systems. We derive rank conditions that the structural parameters of the model must satisfy in order for filtering and smoothing algorithms to operate correctly. We also study the identifiability of the model parameters by characterizing the set of models that… (More)

We study a simple linear regression problem for grouped variables; we are interested in methods which jointly perform estimation and variable selection, that is, that automatically set to zero groups of variables in the regression vector. The Group Lasso (GLasso), a well known approach used to tackle this problem which is also a special case of Multiple… (More)

ÐWe describe an algorithm for reconstructing three-dimensional structure and motion causally, in real time from monocular sequences of images. We prove that the algorithm is minimal and stable, in the sense that the estimation error remains bounded with probability one throughout a sequence of arbitrary length. We discuss a scheme for handling occlusions… (More)

We pose the problem of recognizing different types of human gait in the space of dynamical systems where each gait is represented. Established techniques are employed to track a kinematic model of a human body in motion, and the trajectories of the parameters are used to learn a representation of a dynamical system, which defines a gait. Various types of… (More)

We analyze the observability of the continuous and discrete states of a class of continuous-time linear hybrid systems. We derive necessary and sufficient conditions that the structural parameters of the model must satisfy in order for filtering and smoothing algorithms to operate correctly. Our conditions are simple rank tests that exploit the geometry of… (More)