RESUMEN

The backscatter coefficient is a fundamental property of tissues, much like the attenuation and sound speed. From the backscatter coefficient, different scatterer properties describing the underlying tissue can be used to characterize tissue state. Furthermore, because the backscatter coefficient is a fundamental property of a tissue, estimation of the backscatter coefficient should be able to be computed with system and operator independence. To accomplish system- and operator-independent estimates of the backscatter coefficient, a calibration spectrum must be obtained at the same system settings as the settings used to scan a tissue. In this chapter, we discuss three approaches to obtaining a calibration spectrum and compare the engineering tradeoffs associated with each approach. In addition, methods for reducing deterministic noise in the backscatter coefficient spectrum are considered and implementation of these techniques is discussed.

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RESUMEN

In the field of sensor signal processing, windows are time-/frequency-domain weighting functions that are widely applied to reduce the well-known Gibbs oscillations. Conventional methods generally control the spectral characteristics of windows by adjusting several of the parameters of closed-form expressions. Designers must make trade-offs among the mainlobe width (MW), the peak sidelobe level (PSL), and sometimes the sidelobe fall-off rate (SLFOR) of windows by carefully adjusting these parameters. Generally, not all sidelobes need to be suppressed in specified applications. In this paper, a novel method, i.e., the inverse of the shaped output using the cyclic algorithm (ISO-CA), for designing window functions with flexible spectral characteristics is proposed. Simulations are conducted to test the effectiveness, flexibility and versatility of the method. Some experiments based on real measured data are also presented to demonstrate the practicability. The results show that the window functions generated using the cyclic algorithm (CA) yield better performance overall than the windows of conventional methods, achieving a narrower MW, a lower PSL, and a controllable SLFOR. In addition, steerable sidelobes over specified regions can be acquired both easily and flexibly while maintaining the original properties of the initial window as much as possible.

RESUMEN

The adjoint method shows an efficient way to incorporate inverse dynamics to engineering multibody applications, as, e.g., parameter identification. In case of the identification of parameters in oscillating multibody systems, a combination of Fourier analysis and the adjoint method is an obvious and promising approach. The present paper shows the adjoint method including adjoint Fourier coefficients for the parameter identification of the amplitude response of oscillations. Two examples show the potential and efficiency of the proposed method in multibody dynamics.