Enhancing Q-Factor in a Biquadratic Bandpass Filter Implemented with Opamps

Abstract

Active filter design is a mature topic that provides good solutions that can be implemented using discrete devices or integrated circuit technology. For instance, when the filter topologies are implemented using commercially available operational amplifiers (opamps), one can explore varying circuit parameters to tune the central frequency or enhance the quality (Q) factor. We show the addition of a feedback loop in the signal flow graph of a biquadratic filter topology, which enhances Q and highlights that a sensitivity analysis can be performed to identify which circuit elements influence central frequency, Q, or both. In this manner, we show the opamp-based implementation of a biquadratic bandpass filter, in which Q is enhanced through performing a sensitivity analysis for each circuit element. Equations for the central frequency and Q are provided to observe that there is not a direct parameter that enhances them, but we show that from sensitivity analysis one can identify the circuit elements that better enhance Q-factor.

1 V Tunable High-Quality Universal Filter Using Multiple-Input Operational Transconductance Amplifiers

“…However, these configurations cannot benefit from independent and electronic control of the quality factor and the natural frequency and cannot provide a high-quality (high-Q) filter. In modern applications, high-Q filters are strictly desirable for processing weak signals, such as the detection, measurement, and quantification of biomedical signals [48,49]. The bio-signal has the attributes of a low amplitude and a low frequency (≤10 kHz).…”

SET Pulse Characterization and SER Estimation in Combinational Logic with Placement and Multiple Transient Faults Considerations

“…Also, a new metric for the quantification of gate sensitivity is introduced, which is based on the impact that the three masking effects have on SET propagation up to the sequential components. Estimation of sensitivity is helpful for evaluating the variations of the circuit elements, as was done for example in the design of filters [9]. Extensive simulation results are presented for a variety of ISCAS' 89 benchmark circuits.…”

Models and algorithms for Soft Error Rate estimation in ICs

“…Therefore, there are many approaches, which characterize failures caused in terrestrial circuits and measure SER cell libraries in terms of FIT [22]. Furthermore, an accurate SER estimation is obtained basing on Monte-Carlo simulations and considering ICs layout information [23]. For the modeling of the ICs reliability, Monte-Carlo is a widely-used method utilized to characterize circuit behavior [24,25].…”

“…Next, the circuit is divided into grids (line 15), and for each one, the injection of particle strikes, with different energy at random grid points, generates multiple glitches, via the ERROR_GEN function (lines [19][20][21][22][23]. Something that should be underlined is that the size of each circuit determines the number of grids.…”