Complex Hilbertian Structures on Stable Linear Dynamical Systems

Learning Stable Linear Dynamical Systems Learning Stable Linear Dynamical Systems

Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learning stable linear dynamical systems: we formulate an approximation of the problem as a convex program, start with a solution to a relaxed version of the program, and incrementally add constraints to improve stability. ...

Complex fuzzy linear systems

observational dynamical systems

چکیده در این پایاننامه ابتدا فضاهای متریک فازی را به صورت مشاهدهگرایانه بررسی میکنیم. فضاهای متریک فازی و توپولوژی تولید شده توسط این متریک معرفی شدهاند. سپس بر اساس فضاهایی که در فصل اول معرفی شدهاند آشوب توپولوژیکی، مینیمالیتی و مجموعههای متقاطع در شیوههای مختلف بررسی شده- اند. در فصل سوم مفهوم مجموعههای جاذب فازی به عنوان یک مفهوم پایهای در سیستمهای نیم-دینامیکی نسبی، تعریف شده است. ...

jordan c-dynamical systems

in the first chapter we study the necessary background of structure of commutators of operators and show what the commutator of two operators on a separable hilbert space looks like. in the second chapter we study basic property of jb and jb-algebras, jc and jc-algebras. the purpose of this chapter is to describe derivations of reversible jc-algebras in term of derivations of b (h) which are we...

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learning stable linear dynamical systems: we formulate an approximation of the problem as a convex program, start with a solution to a relaxed version of the program, and incrementally add constraints to improve stability. ...