Vector Fitting (VF) has been introduced as a partial-fraction basis response fitting methodology for over a decade. Because of its reliability and versatility, VF has been applied and extended to a number of areas. In this book chapter, we will discuss the applications of VF in the context of macromodeling of linear structures in signal/power integrity analyses. We will also discuss main featur...

Acquisition of the standard plane is the prerequisite of biometric measurement and diagnosis during the ultrasound (US) examination. In this paper, a new algorithm is developed for the automatic recognition of the fetal facial standard planes (FFSPs) such as the axial, coronal, and sagittal planes. Specifically, densely sampled root scale invariant feature transform (RootSIFT) features are extr...

A significant aspect of reasoning about physical situations involves analysis of the interaction of physical parameters that have both magnitude and direction . There have been some attempts to model motion and rotation in two dimensions, but none of these approaches have been extended to general vector analysis . Humans, however, are exceptionally good in reasoning about direction and motion. ...

In this paper, a novel scheme for vector quantization (VQ) is proposed. A file called visible index file is used to record the coding result. The decompressed image reconstructed from the visible index file is the same as the one recovered using traditional VQ index file; however, the visible index file looks like the original image, and is therefore more convenient for the management of index ...

A modification of a classical Predictive Vector Quantization (PVQ) technique with switched-adaptive prediction for line spectrum frequencies (LSF) quantization is proposed in this paper, enabling significant reduction in complexity. Lower complexity is achieved through use of higher number of switched prediction matrices but with reduced number of their nonzero elements. The structures of such ...

This paper offers new insights into the processes of firm growth by applying a reduced-form vector autoregression (VAR) model to longitudinal panel data on French manufacturing firms. We observe the co-evolution of key variables such as growth of employment, sales, and gross operating surplus, as well as growth of multifactor productivity. It seems that employment growth is negatively associate...

THE numerous investigations now being conducted in vectorcardiography will undoubtedly clarify many nebulous aspects of clinical electrocardiography and will improve present methods of teaching. Yet, with the exception of superiority in demonstrating subtle differences in the phase of •electrical events occurring in the heart, the method in its present state of development does not appear to pr...

The symptom courses of 84 schizophrenia patients (mean age: 24.4 years; mean previous admissions: 1.3; 64% males) of a community-based acute ward were examined to identify dynamic patterns of symptoms and to investigate the relation between these patterns and treatment outcome. The symptoms were monitored by systematic daily staff ratings using a scale composed of three factors: psychoticity, e...

In this paper we propose a strategy for forecasting the term structure of interest rates which may produce significant gains in predictive accuracy. The key idea is to use the restrictions implied by Affine Term Structure Models (ATSM) on a vector autoregression (VAR) as prior information rather than imposing them dogmatically. This allows to account for possible model misspecification. We appl...

In a dynamical system the singular vector (SV) indicates which perturbation will exhibit maximal growth after a time interval tau . We show that in systems with spatiotemporal chaos the SV exponentially localizes in space. Under a suitable transformation, the SV can be described in terms of the Kardar-Parisi-Zhang equation with periodic noise. A scaling argument allows us to deduce a universal ...