New Free-Space Multistage Optical Interconnection Network and its Matrix Theory

A new free-space multistage optical interconnection network which is called the Comega interconnection network is presented. It has the same topological construction for the cascade stages of the Comega interconnection. The concept of the left Comega and the right Comega interconnection networks are given to describe the whole Comega interconnection network. The matrix theory for the Comega interconnection network is presented. The route controlling of the Comega interconnection network is decided based on the matrix analysis. The node switching states in cascade stages of the 8 by 8 Comega interconnection network for the route selection are given. The data communications between arbitrary input channel with arbitrary output channel can be performed easily

Modeling the Volatility of the Heath-Jarrow-Morton Model: A Multi-Factor GARCH Analysis

Based on the nonparametric study of Pearson and Zhou (1999), a parametric HJM model is developed for the forward rate volatility. It allows the volatility of the forward rate with different maturities to react in a different way with the level of forward rate and the forward spread. Specifically, the proposed forward rate volatility function is imbedded into GARCH family models and compared with several widely used HJM volatility specifications. It is shown that the proposed volatility specification performs the best. It is also confirmed that the volatility of forward rate with different maturities depends on the forward rate and the forward spread in a different way.published or submitted for publicationnot peer reviewe

A Nonparametric Analysis of the Forward Rate Volatilities

Heath, Jarrow, and Morton (1992) present a general framework for modeling the term structure of interest rates which nests most other models as special cases. In their framework, the dynamics of the term structure and the prices of derivative instruments depend only upon the initial term structure and the forward rate volatility functions. Despite their importance, there has been little empirical work studying the forward rate volatility functions. This paper begins to fill this gap by estimating some nonparametric models of the forward rate volatilities. In a univariate model, the form of the forward rate volatility function differs for different maturities, and for some maturities appears not to be a monotonic function of the level of the forward rate. In a bivariate model, a measure of the ???slope??? of the term structure seems to have an important impact on the volatility. These results differ from the simple models that have been proposed and used in the literature.published or submitted for publicationnot peer reviewe

Nonparametric and Parametric Analyses on the Forward Rate Volatilities and Their Implications on Interest Rate Options Pricing

110 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.Based on the results obtained in the nonparametric analysis, this paper proposes an HJM volatility model and estimates it in the GARCH-family models. The proposed volatility model is compared with four alternative HJM models and shown to perform well both in capturing the volatility movement and in American options pricing.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Nonparametric and Parametric Analyses on the Forward Rate Volatilities and Their Implications on Interest Rate Options Pricing

110 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.Based on the results obtained in the nonparametric analysis, this paper proposes an HJM volatility model and estimates it in the GARCH-family models. The proposed volatility model is compared with four alternative HJM models and shown to perform well both in capturing the volatility movement and in American options pricing.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Distributed model predictive control for central heating of high-rise residential buildings

Central heating system faults affect building energy consumption and indoor thermal comfort significantly. To aim at the balance between thermal comfortable and energy-saving of the heating system for high-rise residential buildings, this paper proposes a method for the central heating system of high-rise residential buildings based on distributed model predictive control. The method analyzes the coupling factors between adjacent rooms’ temperature. Based on the state space method, a multivariable indoor temperature model is established and verified. The distributed model predictive control method is used to control and optimize the indoor temperature, and the load distribution of the circulating water pump in the heat exchange station is optimized according to the predicted heat demand. The results demonstrate that the indoor temperature after distributed model predictive control can stable near the set value. Compared with the centralized control methods, the proposed methodology can reduce energy consumption by 14.28%. Meanwhile, the efficiency of water pumps is increased by 16.74% after using the distributed control strategy