The induced generalized OWA operator

We present the induced generalized ordered weighted averaging (IGOWA) operator. It is a new aggregation operator that generalizes the OWA operator by using the main characteristics of two well known aggregation operators: the generalized OWA and the induced OWA operator. Then, this operator uses generalized means and order inducing variables in the reordering process. With this formulation, we get a wide range of aggregation operators that include all the particular cases of the IOWA and the GOWA operator, and a lot of other cases such as the induced ordered weighted geometric (IOWG) operator and the induced ordered weighted quadratic averaging (IOWQA) operator. We further generalize the IGOWA operator by using quasi-arithmetic means. The result is the Quasi-IOWA operator. Finally, we also develop a numerical example of the new approach in a financial decision making problem

Role of honesty and confined interpersonal influence in modelling predilections

Classical models of decision-making do not incorporate for the role of influence and honesty that affects the process. This paper develops on the theory of influence in social network analysis. We study the role of influence and honesty of individual experts on collective outcomes. It is assumed that experts have the tendency to improve their initial predilection for an alternative, over the rest, if they interact with one another. It is suggested that this revised predilection may not be proposed with complete honesty by the expert. Degree of honesty is computed from the preference relation provided by the experts. This measure is dependent on average fuzziness in the relation and its disparity from an additive reciprocal relation. Moreover, an algorithm is introduced to cater for incompleteness in the adjacency matrix of interpersonal influences. This is done by analysing the information on how the expert has influenced others and how others have influenced the expert

Role of honesty and confined interpersonal influence in modelling predilections

Classical models of decision-making do not incorporate for the role of influence and honesty that affects the process. This paper develops on the theory of influence in social network analysis. We study the role of influence and honesty of individual experts on collective outcomes. It is assumed that experts have the tendency to improve their initial predilection for an alternative, over the rest, if they interact with one another. It is suggested that this revised predilection may not be proposed with complete honesty by the expert. Degree of honesty is computed from the preference relation provided by the experts. This measure is dependent on average fuzziness in the relation and its disparity from an additive reciprocal relation. Moreover, an algorithm is introduced to cater for incompleteness in the adjacency matrix of interpersonal influences. This is done by analysing the information on how the expert has influenced others and how others have influenced the expert

Razvoj nove klase ortogonalnih filtara s primenom u modeliranju, analizi i sintezi sistema za diferencijalnu impulsno kodnu modulaciju

This PhD dissertation deals with development of new classes of orthogonal filters based on symmetric transformation of their poles to zeroes and vice versa. The filters based on reciprocal transformation are developed and the generalized Malmquist filters orthogonal with respect to a special inner product are designed in this way. The orthogonal filters by using bilinear transformation, including several classes of classical orthogonal cascade filters (Legendre, Laguerre, Müntz-Legendre, Malmquist), are also designed. These filters are practically realized both in analogue and digital techniques. The main quality of these filters is a possibility of adaptive adjustment of filter parameters, i.e. parameters of bilinear transformation, achieving the best filter performances. The final result of this part of research is a wide range of applications of these filters in identification, modelling, analysis, and design of technical systems. The analogue versions of filters are applied in modelling of the system for rubber strip cooling in tyre industry, and their digital versions in modelling of telecommunication system for differential pulse code modulation (DPCM system). It is verified that the models obtained by using these new filters are of higher quality than the models based on classical filters. The other part of research in PhD dissertation refers to the mentioned DPCM system. A complete analysis of DPCM system with arbitrary order predictor is performed for the first time. This relates to the consideration of stability by classical approach, as well as to stochastic stability analysis. The analysis of robust stability by using Kharitonov method is also performed for both deterministic and stochastic case, as well as for low- and high orders of predictors. The parametric sensitivity related to different order-predictors coefficients is also analyzed