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Six novel first-order filters with voltage input, voltage and current outputs employing a single fully differential current conveyor are proposed, three of which are canonical. All the circuits employ a grounded capacitor; and realize all-pass, low-pass and/or high-pass functions. Some circuits provide five distinct first-order functions or six functions with additional output stages. The proposed circuits are verified through computer simulation results.

The paper introduces a new versatile universal biquadratic configuration based on two fully differential second generation current conveyors without need of input matching conditions. The proposed circuit consists of two fully differential second generation current conveyors, four resistors and two grounded capacitors. The proposed biquad configuration provides all five standard filtering responses: low-pass, high-pass, band-pass, band-reject and all-pass in voltage-mode, transadmittance-mode, current-mode and transimpedance-mode. The proposed circuit is single-input multiple-outputs type, so all responses are available simultaneously. Moreover, extra inverting amplifier and double-type amplifier are also not required in the proposed circuit for any filtering response. The nonideal and parasitic effects of fully differential second generation current conveyor on the proposed circuit have also been investigated. HSPICE simulation results have been incorporated to validate the proposal.

In this paper, a new filtering method is presented to remove the Rician noise from magnetic resonance images (MRI) acquired using single coil MRI acquisition system. This filter is based on nonlocal neutrosophic set (NLNS) approach of Wiener filtering. A neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. Now, we apply the neutrosophic set into image domain and define some concepts and operators for image denoising. First, the nonlocal mean is applied to the noisy MRI. The resultant image is transformed into NS domain, described using three membership sets: true (T), indeterminacy (I) and false (F). The entropy of the neutrosophic set is defined and employed to measure the indeterminacy. The -Wiener filtering operation is used on T and F to decrease the set indeterminacy and to remove the noise. The experiments have been conducted on simulated MR images from Brainweb database and clinical MR images. The results show that the NLNS Wiener filter produces better denoising results in terms of qualitative and quantitative measures compared with other denoising methods, such as classical Wiener filter, the anisotropic diffusion filter, the total variation minimization and the nonlocal means filter. The visual and the diagnostic quality of the denoised image are well preserved.