One of the appealing cases of the neuromorphic research area is the implementation of biological neural networks. The current study offers Multiplierless Hodgkin-Huxley Model (MHHM). This modified model may reproduce various spiking behaviors, like the biological HH neurons, with high accuracy. The presented modified model, in comparison to the original HH model, due to its exact similarity to the original model, has more top performances in the case of FPGA saving and more achievable frequency (speed-up). In this approach, the proposed model has a 69 % saving in FPGA resources and also the maximum frequency of 85 MHz that is more than other similar works. In this modification, all spiking behaviors of the original model have been generated with low error calculations. To validate the MHHM neuron, this proposed model has been implemented on digital hardware FPGA. This approach demonstrates that the original HH model and the proposed model have high similarity in terms of higher performance and digital hardware cost reduction.

In this article, a novel microstrip lowpass filter (LPF) with specifications such as sharp cut-off, wide stopband, low insertion loss and high return loss using tapered resonator is presented. The LPF has cut-off frequency of 1.11 GHz, where unwanted harmonics are suppressed by novel tapered cells. The bandwidth is enhanced, and the size is reduced as compared to the conventional tapered filter. The transition band is approximately 0.29 GHz from 1.11 to 1.4 GHz with corresponding attenuation levels of –3 and –20 dB, respectively. The stopband with greater than –20 dB rejection is from 1.4 to 8.9 GHz, insertion loss in the passband is less than 0.1 dB, return loss is less than –18 dB and the overall size of the filter is 0.12 × 0.073 λ_g. The proposed filter is fabricated and measured. The simulation and measurement results are in good agreement. This LPF is designed for microwave communication applications, especially wireless video transmitters.