Optimal spectral bandwidth for long memory

For long range dependent time series with a spectral singularity at frequency zero, a theory for optimal bandwidth choice in non-parametric analysis ofthe singularity was developed by Robinson (1991b). The optimal bandwidths are described and compared with those in case of analysis of a smooth spectrum. They are also analysed in case of fractional ARIMA models and calculated as a function of the self similarity parameter in some special cases. Feasible data dependent approximations to the optimal bandwidth are discussed

Perceptually smooth timbral guides by state-space analysis of phase-vocoder parameters

Sculptor is a phase-vocoder-based package of programs that allows users to explore timbral manipulation of sound in real time. It is the product of a research program seeking ultimately to perform gestural capture by analysis of the sound a performer makes using a conventional instrument. Since the phase-vocoder output is of high dimensionality — typically more than 1,000 channels per analysis frame—mapping phase-vocoder output to appropriate input parameters for a synthesizer is only feasible in theory

Information compression in the context model

The Context Model provides a formal framework for the representation, interpretation, and analysis of vague and uncertain data. The clear semantics of the underlying concepts make it feasible to compare well-known approaches to the modeling of imperfect knowledge like that given in Bayes Theory, Shafer's Evidence Theory, the Transferable Belief Model, and Possibility Theory. In this paper we present the basic ideas of the Context Model and show its applicability as an alternative foundation of Possibility Theory and the epistemic view of fuzzy sets

Optimal Disease Eradication

Using a dynamic model of the control of an infectious disease, we derive the conditions under which eradication will be optimal. When eradication is feasible, the optimal program requires either a low vaccination rate or eradication. A high vaccination rate is never optimal. Under special conditions, the results are especially stark: the optimal policy is either not to vaccinate at all or to eradicate. Our analysis yields a cost-benefit rule for eradication, which we apply to the current initiative to eradicate polio.Eradication of infectious diseases; vaccination; control theory; cost-benefit analysis; poliomyelitis

Optimal Disease Eradication

Using a dynamic model of the control of an infectious disease, we derive the conditions under which eradication will be optimal. When eradication is feasible, the optimal program requires either a low vaccination rate or eradication. A high vaccination rate is never optimal. Under special conditions, the results are especially stark: the optimal policy is either not to vaccinate at all or to eradicate. Our analysis yields a cost-benefit rule for eradication, which we apply to the current initiative to eradicate polio.Eradication of infectious diseases, Vaccination, Control theory, Cost-benefit analysis, Poliomyelitis

Distance to the Nearest Stable Metzler Matrix

This paper considers the non-convex problem of finding the nearest Metzler matrix to a given possibly unstable matrix. Linear systems whose state vector evolves according to a Metzler matrix have many desirable properties in analysis and control with regard to scalability. This motivates the question, how close (in the Frobenius norm of coefficients) to the nearest Metzler matrix are we? Dropping the Metzler constraint, this problem has recently been studied using the theory of dissipative Hamiltonian (DH) systems, which provide a helpful characterization of the feasible set of stable matrices. This work uses the DH theory to provide a block coordinate descent algorithm consisting of a quadratic program with favourable structural properties and a semidefinite program for which recent diagonal dominance results can be used to improve tractability.Comment: To Appear in Proc. of 56th IEEE CD