In this letter, a microstrip negative-group-delay (NGD) admittance inverter (J-inverter) is proposed to implement a self-equalized linear-phase absorptive bandpass filter (ABPF). It is revealed that this NGD J-inverter, being composed of a coupled-line loaded with a lumped resistor and an open-circuited stub, has an NGD pit in its frequency response. The superposition of the NGD pits associated with a specific number of the NGD J-inverters is utilized to counterbalance the group delay (GD) peaks at the lower and upper edge of the ABPF passband. A three-order ABPF prototype with a passband of 1.5-2.5 GHz is designed using six NGD J-inverters. Measured GD fluctuation within the 3-dB bandwidth is reduced to 0.18 from 0.59 ns compared with the ABPF using the conventional λ /4 J-inverter. The sharpness of the out-band roll-off has been retained. The measured input-output return loss is better than 12 dB over 0.6-3.5 GHz.

A bandpass filter (BPF) using dual-band negative group delay equalizers (NGDEs) for extending linear-phase bandwidth is reported in this letter. This dual-band NGDE is synthesized based on a coupling-routing-diagram approach and implemented by a parallel-coupled three-line structure. By cascading two NGDEs to the input and output ports of a conventional BPF, the dual-band NGD characteristic associated with NGDEs is applied to counteract the group delay (GD) peaks at the transition bands of the conventional BPF. A microstrip linear-phase BPF prototype in the S -band is designed. Compared with the conventional BPF, the GD fluctuation of the equalized BPF is decreased by 75% from 0.4 to 0.1 ns within the passband of 1.50–2.50 GHz, while no obvious degradation of out-of-band suppression is observed and the overall time delay is not increased. The devised BPF achieves a linear-phase characteristic in the whole passband with a compact circuit size of 0.32 $\uplambda_{\text{g}}^{2}$ .

Absorptive bandpass filters (ABPFs) are highly attractive in modern microwave communication systems due to their ability to internally absorb the harmful stopband RF-power reflections. This paper reports an approach to designing quasi-elliptic ABPFs with ultra-wide reflectionless range, enhanced selectivity, and compact size. The method is realized based on a fourth-order quasi-elliptic absorptive lowpass filter (ALPF) prototype with a simplified structure. This ALPF prototype exhibits both good impedance-matching over the whole normalized frequency domain and an adjustable transmission zero close to the passband. By applying an equivalent impedance transformer model, a coupled-line-based ABPF scheme is devised from the ALPF prototype, which eliminates conventional dispersive transmission line inverters, resulting in an ultra-wide reflectionless range and a compact size. Closed-form equations are derived to support the filter synthesis. A 2.45 GHz microstrip ABPF with 30% fractional bandwidth is designed for verification. The measured minimum in-band insertion loss is 0.83 dB and the reflectionless range of return loss better than 10 dB is from DC to 12.88 GHz. Both the upper and lower stopband suppression exceed 20 dB, with the upper stopband extending up to 6.80 GHz. The upper and lower out-of-band roll-off rates are 93.9 and 121.4 dB/GHz, respectively. The overall circuit size is 0.12 λ_g².

This article presents a generative model for the inverse design of dual-band filters based on a type of modified complementary split-ring resonator (CSRR). It consists of a series of convolutional neural networks that incorporate the conditional deep convolutional generative adversarial network (GAN) technique. The filters are designed by etching the modified CSRRs on the surface of substrate-integrated waveguides. This design allows us to achieve two passbands with a compact size. In this GAN-based generative model, the CSRRs are represented as two-dimensional matrices. Each matrix corresponds to a training sample of the designed filter, and its S-parameters are extracted through an HFSS simulation. Both the matrices and the S-parameters are fed into the model as the training datasets. Different CSRRs with various sizes are employed for a wider applicable frequency band. Normalized matrices and normalized S-parameters are utilized to simplify the complex generative model resulting from the variations in CSRR sizes. The effectiveness of the generative model is validated through four design examples of dual-band filters, with their center frequencies located within 5 to 18 GHz. The inference time for each design is approximately 18.5 min. The measurement results of the fabricated filters are in good agreement with the simulation ones.