Search
Search Results
-
Optimal stabilization of linear stochastic systems
Having introduced and motivated our concepts of stochastic control systems in the previous chapter we now turn to optimal and suboptimal... -
Linear map**s on ordered vector spaces
Before we can start to analyze the generalized Riccati operators derived in the previous chapter, we have to deal with generalized Lyapunov operators... -
Modeling of Fuzzy Data
Fuzzy data are imprecise data obtained from measurements, perception or by interviewing people. Typically, those data are expressed in linguistic... -
Set-valued Data
Since fuzzy sets are generalizations of ordinary sets, we present in this Chapter the essentials of random set theory for statistics. This material... -
Tests of Hypothesis: Means
In many expositions of fuzzy methods, fuzzy techniques are described as an alternative to a more traditional statistical approach. In this chapter,... -
Fuzzy Time Series Analysis and Forecasting
The problem of system modeling and identification has attracted considerable attention during the past decades mostly because of a large number of... -
Fuzzy Statistical Analysis and Estimation
In social science research, many decisions, evaluations, or purposes of evaluations are done by surveys or questionnaires to seek for people’s... -
Aspects of stochastic control theory
In the present chapter, we introduce linear stochastic control systems and the corresponding notions of stability, stabilizability and detectability.... -
Aspects of Statistical Inference
With the background in previous chapters, problems of statistical inference with fuzzy data should be somewhat straightforward in principle! By that... -
Convergence of Random Fuzzy Sets
As in Chapter 5, we view random fuzzy sets as generalizations of random closed sets on R d , or more generally on... -
Random Fuzzy Sets
Statistical models for observations which are numbers or vectors are random variables and random vectors, respectively. Similarly, if the... -
Introduction
First like fuzzy logics are logics with fuzzy concepts, by fuzzy statistics we mean statistics with fuzzy data. Data are fuzzy when they are... -
Hermitian matrices and Schur complements
Throughout the text, $\mathbb{K}$ denotes either the field of real or the... -
Newton’s method
This chapter contains some of our main results. It largely follows the presentation in [49]. Our object is to tackle rational matrix equations of the... -
Solution of the Riccati equation
In Chapter 2 we have discussed various optimal and worst-case stabilization problems for linear stochastic control systems and reformulated them in... -
Scaling limit of the disordered generalized Poland–Scheraga model for DNA denaturation
The Poland–Scheraga model, introduced in the 1970s, is a reference model to describe the denaturation transition of DNA. More recently, it has been...
-
An extension of the Poincaré–Birkhoff Theorem to systems involving Landesman–Lazer conditions
We provide multiplicity results for the periodic problem associated with Hamiltonian systems coupling a system having a Poincaré–Birkhoff twist-type...
-
Failure of almost uniform convergence for noncommutative martingales
In this paper, we provide a counterexample to show that in sharp contrast to the classical case, the almost uniform convergence may not happen for...
-
Well-Posedness for Path-Distribution Dependent Stochastic Differential Equations with Singular Drifts
Well-posedness is derived for singular path-distribution dependent stochastic differential equations (SDEs) with non-degenerate noise, where the...