Abstract: The disclosure provides a method for assembling and interconnecting FBAR filter and an electronic device. The method includes constructing an equivalent circuit model of an assembled FBAR filter according to a circuit model of a filter chip and the grounding circuit of the FBAR filter; modeling, simulating and calculating the grounding circuit to extract parasitic parameters corresponding to the grounding pad and a grounding bond-wire of the grounding circuit, respectively; feedbacking the parasitic parameters back into the equivalent circuit model, and using the circuit simulation software to obtain an S parameter of the filter; adjusting the parasitic parameters of the grounding circuit to optimize an S parameter performance of the FBAR filter: obtaining an optimal assembly configuration of the FBAR filter to guide the assembly. The parasitic parameters include a parasitic inductance of the grounding bond-wire and a parasitic capacitance and parasitic inductance of the grounding pad.

Abstract: Apparatuses, systems, and techniques to train/use one or more neural networks. In at least one embodiment, a processor comprises one or more circuits to cause neural network training information to be aggregated based, at least in part, on contribution of the neural network training data and one or more performance metrics of the neural network.