Identifiability of slowly varying systems

A system is conceived of as being slowly varying if it changes slowly enough to permit identification to within a specified error. A generic model is developed to study the identifiability and identification of slowly varying systems. The model is suitable for a large variety of nonlinear, time-varying, causal, bounded memory systems; it has finitely many parameters and is linear in its parameters. Results are obtained with the use of this general model that give guaranteed accuracy of identification as a function of the prior knowledge of the unknown system, the maximum rate of time variation of the system, and the characteristics of output observation noise. To derive these results, a recursive estimation procedure is developed for time-discrete linear dynamical system structures in which the observation noise is statistical but the dynamic equation noise is nonstatistical and is known only to be bounded.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/21640/1/0000024.pd

Assumption without representation: the unacknowledged abstraction from communities and social goods

We have not clearly acknowledged the abstraction from unpriceable “social goods” (derived from communities) which, different from private and public goods, simply disappear if it is attempted to market them. Separability from markets and economics has not been argued, much less established. Acknowledging communities would reinforce rather than undermine them, and thus facilitate the production of social goods. But it would also help economics by facilitating our understanding of – and response to – financial crises as well as environmental destruction and many social problems, and by reducing the alienation from economics often felt by students and the public

Modeling And Identification Of Relatively Slowly Varying Systems.

Ph.D.Systems designUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/188764/2/7520342.pd

Least squares and linear unbiased minimum variance estimation in Euclidean space and Hilbert space

http://deepblue.lib.umich.edu/bitstream/2027.42/4907/5/bac2405.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/4907/4/bac2405.0001.001.tx

VHF-UHF phased array techniques

http://deepblue.lib.umich.edu/bitstream/2027.42/6411/3/bad0627.0001.001.txthttp://deepblue.lib.umich.edu/bitstream/2027.42/6411/5/VHF-UHF Phased Array Techniques.pd