Simple Three-Input Single-Output Current-Mode Universal Filter Using Single VDCC

This paper presents a second-order current-mode filter with three-inputs and single-output current using single voltage differencing current conveyors (VDCC) along with one resistor and two grounded capacitors. The design of presented filter emphasizes on the use of a single active element without the multiple terminals VDCC which is convenient to implement the VDCC using commercially available IC for the practical test. Also, it can reduce the current tracking error at current output port and can reduce the number of transistor in the VDCC. The proposed filter can realize all the five generic filter responses, namely, band-pass (BP), band-reject (BR), low-pass (LP), high-pass (HP), and all-pass (AP) functions from the same configuration under various conditions in terms of three input current signals. Furthermore, the natural frequency and quality factor are electronically controlled. The output current node exhibits high impedance. Besides, the non-ideal case is also investigated. The simulation and experimental results using VDCC constructed from commercially available IC can validate the theoretical analyses.

CLASS FORCING, THE FORCING THEOREM AND BOOLEAN COMPLETIONS

The forcing theorem is the most fundamental result about set forcing, stating that the forcing relation for any set forcing is definable and that the truth lemma holds, that is everything that holds in a generic extension is forced by a condition in the relevant generic filter. We show that both the definability (and, in fact, even the amenability) of the forcing relation and the truth lemma can fail for class forcing.In addition to these negative results, we show that the forcing theorem is equivalent to the existence of a (certain kind of) Boolean completion, and we introduce a weak combinatorial property (approachability by projections) that implies the forcing theorem to hold. Finally, we show that unlike for set forcing, Boolean completions need not be unique for class forcing.

Single Active Element Based Voltage-Mode Multifunction Filter

The paper presents a new voltage-mode multifunction filter. The proposed filter employs single modified fully differential second generation current conveyor (FDCCII), two grounded capacitors, and three resistors. The proposed circuit enjoys the employment of two grounded capacitors (attractive for absorbing shunt parasitic capacitance and ideal for IC implementation). The proposed circuit provides all five generic filter responses (low pass (LP), high pass (HP), band pass (BP), notch (NH), and all pass (AP) filter responses) simultaneously with single input. The novel proposed filter has low active and passive sensitivities. A number of time domain and frequency domain simulation results depicted through PSPICE using 0.18 µm TSMC process parameters are included to validate the theory. The proposed circuit is expected to enhance the existing knowledge on the subject.

A Threshold with Hysteresis

Thresholding is perhaps one of the most basic techniques in image processing. The Insight Toolkit (ITK) includes several threshold filters ranging from simple ones to Otsu based thresholding. Deep into the implementation of the Canny edge detection filter, ITK includes an implementation of hysteresis thresholding, but unfortunately this method can not be used as a generic filter. This paper presents an implementation of the hysteresis thresholding filter that can be used as a standalone ITK filter.

Efficient contour detection in binary and label images

ly in ITK, the only way to find the contour of the objects in a binary image is to use the BinaryErodeImageFilter, with a kernel of radius 1. This filter is a generic filter, made to support any shape and size of structuring element, and thus is not optimized for the particular case needed to detect the contours. Moreover, that filter is not multithreaded, so it can’t get the performance improvements allowed by the multiprocessor systems. As a result, the contour detection can be quite time consuming currently – for example, in SignedMaurerDistanceMapImageFilter, the contour detection takes about 33% of the execution time. This contribution comes with a new filter which highly improve the performance of the contour detection in the binary image, and a second filter which allow the detection of the countours in label images with similar performance.