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Neural networks (NNs) are quite attractive in creating surrogate models for many signal integrity (SI) applications. NN-based surrogate models offer the benefits of reducing the design cycle time and providing the designer with a quick prototype that can efficiently analyze the performance of the SI task. This article, therefore, proposes a new end-to-end learning approach for surrogate modeling using complex-valued NNs, incorporating higher functionality and better representation. This approach introduces a deep complex dense network ( $\mathbb {C}$ DNet), which is built with complex dense blocks to support complex operations using complex-valued weights, and a physically consistent layer to enforce passivity and causality constraints. We also present a robust inverse multiobjective optimization method to minimize the modeling error and optimize the design space parameters. The results show that our model outperforms state-of-the-art deep surrogate models when tasked with forward and inverse learning for a relatively small amount of data. The effectiveness of the proposed approach is demonstrated through two SI design applications, where the model is used to predict broadband $S$ -parameters and obtain optimal design space parameters given the desired target specifications.

This paper describes the demonstration of a low loss substrate (laminated glass) for high-frequency transmission using a dry film build-up material with low loss tangent (Df). This paper also evaluates filter characteristics and dielectric characteristics of the substrate in the mm-Wave band. The advanced low loss dry film build-up material was newly developed, and applicable to high frequency transmission. This material has a Df of 0.0025 at 10 GHz and also exhibits excellent adhesion and electrical reliability required for advanced dielectric materials. In addition, glass was used as a core material in this paper because of its excellent signal transmission characteristics compared to silicon wafers or organic substrates. To demonstrate the benefit of low loss materials for high frequency transmission, passive components for high frequency filter substrates were fabricated using - 6-inch square thin (0.2mm) glass panel with various build-up materials (Material A with a Df of 0.0025, and Material B with a Df 0.0042 at 10 GHz) laminated. Copper wiring patterns on the dielectric layers were fabricated by a semi-additive process (SAP). Circuit patterns with low pass filters and band pass filters were also fabricated. First, transmission characteristics and characteristic impedances were measured to check the electrical performance. The measured lowest transmission loss of < 1.43 dB at 39 GHz were achieved when Material A was applied as the build-up material. Second, biased-highly accelerated stress test (bHAST) was conducted to evaluate the reliability performance of the substrates with two build-up materials, Material A and a conventional material. The test condition was based on the JEDEC level 2 standard. The substrate with Material A retained good insulation properties over 300 hours of bHAST treatment, demonstrating its excellent insulating performance. In summary, Material A has been shown in this paper to exhibit reduced transmission loss in high-frequency filter substrates at millimeter wave frequencies. [ABSTRACT FROM AUTHOR]