Abstract: This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding a jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.
Abstract: In this paper, we present a model and an algorithm for
the calculation of the optimal control limit, average cost, sample size,
and the sampling interval for an optimal Bayesian chart to control
the proportion of defective items produced using a semi-Markov
decision process approach. Traditional p-chart has been widely
used for controlling the proportion of defectives in various kinds
of production processes for many years. It is well known that
traditional non-Bayesian charts are not optimal, but very few optimal
Bayesian control charts have been developed in the literature, mostly
considering finite horizon. The objective of this paper is to develop
a fast computational algorithm to obtain the optimal parameters of a
Bayesian p-chart. The decision problem is formulated in the partially
observable framework and the developed algorithm is illustrated by
a numerical example.
Abstract: The cumulative conformance count (CCC) charts are
widespread in process monitoring of high-yield manufacturing.
Recently, it is found the use of variable sampling interval (VSI)
scheme could further enhance the efficiency of the standard CCC
charts. The average time to signal (ATS) a shift in defect rate has
become traditional measure of efficiency of a chart with the VSI
scheme. Determining the ATS is frequently a difficult and tedious
task. A simple method based on a finite Markov Chain approach for
modeling the ATS is developed. In addition, numerical results are
given.
Abstract: This paper describes the design of a voltage based maximum power point tracker (MPPT) for photovoltaic (PV) applications. Of the various MPPT methods, the voltage based method is considered to be the simplest and cost effective. The major disadvantage of this method is that the PV array is disconnected from the load for the sampling of its open circuit voltage, which inevitably results in power loss. Another disadvantage, in case of rapid irradiance variation, is that if the duration between two successive samplings, called the sampling period, is too long there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit has also been simplified. The proposed circuit does not utilize a microcontroller or a digital signal processor and is thus suitable for low cost and low power applications.