Adaptive IIR filtering based on balanced-realization

Due to low parameter sensitivity for balanced realiza- tions, balanced structure becomes a good candidate for an statespace adaptive infinite impluse response （IIR） filter. Here, using coefficients of the transfer function as the adaptive filtering parameters, a balanced adaptive IIR filtering algorithm is proposed for output-error minimization. The algorithm in the internally balanced realization guarantees that the adaptive IIR filter always minimizes the ratio of maximum-to-minimum eigenvalue of the Grammian matrices at the each iteration. Simulation results are provided to corroborate the proposed algorithm.

Frequency-domain generelaized singular peruturbation method for relative error model order reduction

A new mixed method for relative error model order reduction is proposed. In the proposed method the frequency domain balanced stochastic truncation method is improved by applying the generalized singular perturbation method to the frequency domain balanced system in the reduction procedure. The frequency domain balanced stochastic truncation method, which was proposed in [15] and [17] by the author, is based on two recently developed methods, namely frequency domain balanced truncation within a desired frequency bound and inner-outer factorization techniques. The proposed method in ttiis paper is a carry over of the frequency-domain balanced stochastic truncation and is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency and important system properties. It is shown that some important properties of the frequency domain stochastic balanced reduction technique are extended to the proposed reduction method by using the concept and properties of the reciprocal systems. Numerical results show the accuracy, simplicity and flexibility enhancement of the method.

Balancing the Realization of Ecological,Economic and Social Values of Forests for Sustainable Forest Management

Forests provide multiple ecological,economic and social benefits.A truly sustainable forest management should lead to a balanced realization of these forest values.This paper categorizes the forest resources as appreciating resources and depreciating resources in accordance with the specific form of forest values,and defines them conceptually in regard to the contrasting and competitive nature of these values.Necessary theoretic discussions were then made for the feasibility and operability in terms of t...

Reduced-order Modeling of Human Body for Brain Hypothermia Treatment

Brain hypothermia treatment （BHT） is an active therapy for severe brain injury. It makes the temperature of the brain track a given temperature input curve so as to reduce the risk of tissue damage. BHT requires a brain-temperature control system because of environmental disturbances and changes in the human body. The thermal models of the human body devised so far are usually of a very high order and are not suitable for controlling brain temperature. This paper presents a method of finding a reducedorder thermal model of the human body for use in BHT. It combines minimal realization and balanced realization. Unlike other methods, this method yields a reduced-order model that is based on system theory and that takes the frequency characteristics of human thermal sensation into account. It features high precision in the frequency band for BHT and is suitable for the control of brain temperature.

Recent Advance in Non-Krylov Subspace Model Order Reduction of Interconnect Circuits

Model order reduction of interconnect circuits is an important technique to reduce the circuit complexity and improve the efficiency of post-layout verification process in the nanometer VLSI design. Existing works using the Krylov subspace method are very efficient, but the resulting models are less compact and lack global accuracy. Also, existing methods cannot handle interconnect circuits with large input and output ports. Recent advances in reduction techniques using non-Krylov subspace techniques such as truncated balanced realization （TBR） hold some promise to solve these problems. In this paper, we first review the classic TBR-based reduction methods and then present the recent developments in fast TBR-based reduction and techniques such as PMTBR, SBPOR, and ETBR methods. These newly proposed methods try to avoid the expensive computing steps in traditional TBR methods at some cost to accuracy to boost efficiency and scalability, which is critical to reduce large interconnect parasitics modeled as RLCK circuits. The ETBR method can also reduce circuits with massive ports by considering the input signals. We show the pros and cons of each method and compare them on a set of large interconnect circuits, and finally point to some new research directions for this area.