In modern computing technique, calculation of leading zeros in a data represented as strings of digits is used very often. Those techniques require high speed of the circuit, as well as its fast design. In this paper we propose a design of such a counter, which is applicable to data length of w = 4j bits, for 4 < j ≤ 8. With this solution it is also possible to process longer data, since the suggested technique offers a good modularity. This is very important, considering the current technology scaling trends. In this paper, a delay behavior of the proposed circuit has also been investigated using equations and VHDL simulation based worst-case delay estimation method. The results show a significant improvement of the circuit speed, compared to the known solutions.

Testing switched capacitor circuits is a challenge due to the diversity of the possible faults. A special problem encountered is the synthesis of the test signal that will control and make the fault-effect observable at the test point. The oscillation based method which was adopted for testing in these proceedings resolves that important issue in its nature. Here we discuss the properties of the method and the conditions to be fulfilled in order to implement it in the right way. To achieve that, we have resolved the problem of synthesis of the positive feed-back circuit and the choice of a proper model of the operational amplifier. In that way, a realistic foundation to the testing process was generated. A second order notch cell was chosen as a case-study. Fault dictionaries were developed related to the catastrophic faults of the switches used within the cell. The results reported here are a continuation of our previous work and are complimentary to some other already published.

Oscillation Based Testing (OBT) is an effective and simple solution to the testing problem of continuous time analogue electronic filters. In this paper, diagnosis based on OBT is described for the first time. It will be referred to as OBD. A fault dictionary is created and used to perform diagnosis with artificial neural networks (ANNs) implemented as classifiers. The robustness of the ANN diagnostic concept is also demonstrated by the addition of white noise to the “measured” signals. The implementation of the new concept is demonstrated by testing and diagnosis of a second order notch cell realized with one operational amplifier. Single soft and catastrophic faults are considered in detail and an example of the diagnosis of double soft faults is also given.

Accurate prediction of the short time series with highly irregular behavior is a challenging task found in many areas of modern science. Such data fluctuations are not systematic and hardly predictable. In recent years, artificial neural networks have widely been exploited for those purposes. Although it is possible to model nonlinear behavior of short time series by using ANNs, very often they are not able to handle all events equally well. Therefore, alternative approaches have to be applied. In this study, a new, concurrent, performance-based methodology that combines best ANN topologies in order to decrease the forecasting errors and increase the forecasting certainty is proposed. The proposed approach is verified on three different data sets: the Serbian Gross National Income time series, the municipal traffic flow for a particular observation point, and the daily electric load consumption time series. It is shown that the method can significantly increase the forecasting accuracy of the individual networks, regardless of their topologies, which makes the methodology more applicable. For quantitative comparison of the accuracy of the proposed methodology with that of similar methodologies, a series of additional forecasting experiments that include a state-of-the-art ARIMA modelling and a combination of ANN and linear regression forecasting have been conducted.