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The standard multivariate metrics for semiconductor product yield estimation and prediction in production processes usually assume that the parameters contributing to the yield are all normally distributed. However, the data met in production processes is not always multivariate normal. A variety of methods has been developed for multivariate non-normal data, but these usually rely on no statistical...
The standard metrics for integrated circuits' analysis and characterization in production processes usually assume that the process under investigation is characterized by a normal distribution. However, the data met in practice are not always normal and the yield estimates may be inaccurate. In this paper we propose estimating the yield by using a distribution fitting flow. The selected distribution...
The modern electronic systems have become very complex with a high number of potential factors that may affect the systems' behavior. Sensitivity analysis may be employed to simplify the analysis of such systems and identify the most important factors upfront. The paper introduces two new sensitivity analysis methods based on the measure of entropy, which overcome the limitation of several state-of-the-art...
This paper presents a general procedure for datapath and control design, an example and a proposed laboratory work. The objective of the procedure is to transform a pseudo code (or a code written in a functional programming language) of an algorithm into a synthesizable HDL description. The procedure is general enough to be applied on simple algorithms (a few variables, value assignments and repetitive...
This paper presents a method for synthesizing linear-phase FIR filters capable of implementing magnitude characteristics defined arbitrarily by the user through a set of frequency–magnitude points, filters that are optimized with respect to several criteria. The main idea is to approach the filter synthesis as a multi-objective optimization problem, targeting the minimization of both the peak magnitude...
This paper extensively exhibits the computational procedure and circumstances of the scaling factor used in a recent variable step size normalized least-mean-square (NLMS) adaptation strategy called error-dependent step-size control (EDSC). Applied on Volterra models, it enhances the convergence of conventional methods for the same steady-state misadjustment. Entailed in the variable step-size (VSS)...
This paper presents a method for optimized synthesis of IIR filters with user-defined magnitude response, based on a real-coded genetic algorithm. The application envisaged in this paper is the design of filters for hearing aids, which have to match given human audiograms. Two metrics for the differences between the synthesized and wanted magnitude characteristics are minimized by the optimization...
The robustness of the system response to production factors and operating conditions is a big challenge as the systems grow in complexity and heterogeneity. In this paper, we propose a method that solves the robust parameter design problem. First, we define some cost functions based on the distribution of the system's response and, second, we estimate the dependence of the cost function on the controllable...
Systems grow in complexity but their behavior has to meet the specifications and to be robust in all or most situations and conditions. When variations affect more responses of a system, achieving robustness becomes a hard to fulfill task because different responses may demand concurrent settings for the system's factors. In this paper, we approach multi-response robustness optimization by estimating...
This paper presents an effective technique for generating pairs of in-quadrature sinusoidal signals by using only standard signal generators and oscilloscopes. The proposed method is particularly well suited for measuring the magnitude characteristic of poly-phase filters. An example is presented in some detail: the characterization of a fully differential poly-phase filter integrated in a standard...
The paper focuses on treating and characterizing variations that occur in measurements or that are intrinsic in electronic systems. Methods illustrating basic principles of Design of Experiments such as replication and blocking are implemented and used so that valid and objective conclusions are drawn. Replication is used for three purposes: verifying the metamodel adequacy, defining the confidence...
The paper proposes a novel nonlinear acoustic echo cancellation approach based on adaptive second-order Volterra structures designed to increase the convergence rate of the conventional Volterra filter. Depending on the envelope of the resulting error's absolute value or, if available, on the local noise levels from the enclosure, the variable step sizes are weighted according to the decrease of the...
Real-life systems should perform within tight limits even when affected by uncontrollable factors such as temperature and power supply variations. This paper outlines a methodology for robustness optimization based on the Design of Experiments and metamodelling concepts. The main idea is to derive metamodels of the mean response and its dispersion depending only on control factors; thus, the optimization...
This paper proposes a new updating technique for adaptive Volterra kernels employed as nonlinear models for the identification of unknown feedback paths in acoustic nonlinear echo cancellation tasks. Considering that nonlinear distortions are mainly introduced for high input levels, the effective step size is shaped according to the instantaneous envelope of the excitation signal. The loudspeaker-enclosure-microphone...
The paper presents an acoustic echo cancellation application of three variable step-size Normalized Least Mean Square (NLMS) algorithms: the simple VSS-NLMS (SVSS-NLMS), the new non-parametric (NEW-NPVSS-NLMS) and the practical VSS-NLMS (PVSS-NLMS) algorithms. Simulations were performed in two scenarios: single-talk and double-talk. We will prove that the PVSS-NLMS algorithm can be used in a double-talk...
The paper proposes a nonlinear system identification method that uses a combination of adaptive linear, Volterra and power filters. Adaptation of the kernels is made using a Normalized Least Mean Square algorithm. The method is applied in echo cancellation, where several sources of nonlinearities exist: the overdriven amplifier, the small loudspeaker at high volume, the room with different absorbent...
This paper presents a variable-gain amplifier (VGA) based on transconductors (Gm cells); it consists of two instantiations of the same Gm core and three scaled output stages. The core is optimized for high linearity that is not affected by the gain setting as the gain variation is achieved through a differential current steering scheme. The proposed VGA is well suited for multistandard radio receivers:...
In the paper, an echo canceller based on a system identification scheme with adaptive algorithms is presented. The algorithms consider FIR filters with the taps chosen to minimize an error signal derived from the system according to a stochastic gradient-based method. The following adaptive filters are discussed and simulated in Matlab: classical LMS and its variants: NLMS, VSLMS, VSNLMS and RLS....
Two methods for determining the loop gain of OpAmp-based circuits with series-shunt feedback through simulations are analyzed and compared: the standard method — that involves breaking the feedback loop by inserting an independent voltage source with DC=0 and AC=1 — and a more precise method, based on the Rosenstark theorem. Only the cases for the traditional (voltage-feedback) and the current-feedback...
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