Embedded Thin Film Resistors on BCB by Low-Cost PWB Compatible Electroless Plating by Direct Foil Lamination Transfer Processes

Benzocyclobutene (BCB) has been proposed as a board level dielectric for advanced system-on-package (SOP) module primarily due to its attractive low-loss (for RF application) and thin film (for high density wiring) properties. Realization of embedded resistors on low loss benzocyclobutene (dielectric loss ~0.0008 at > 40 GHz) has been explored in this study. Two approaches, viz, foil transfer and electroless plating have been attempted for deposition of thin film resistors on benzocyclobutene (BCB). Ni-P alloys were plated using conventional electroless plating, and NiCr and NiCrAlSi foils were used for the foil transfer process. This paper reports NiP and NiWP electroless plated embedded resistors on BCB dielectric for the first time in the literature

Novel auditory motivated subband temporal envelope based fundamental frequency estimation algorithm

We address the problem of estimating the fundamental frequency of voiced speech. We present a novel solution motivated by the importance of amplitude modulation in sound processing and speech perception. The new algorithm is based on a cumulative spectrum computed from the temporal envelope of various subbands. We provide theoretical analysis to derive the new pitch estimator based on the temporal envelope of the bandpass speech signal. We report extensive experimental performance for synthetic as well as natural vowels for both realworld noisy and noise-free data. Experimental results show that the new technique performs accurate pitch estimation and is robust to noise. We also show that the technique is superior to the autocorrelation technique for pitch estimation.

Extrema based unwarping for time-varying pitch estimation

We present an extrema based unwarping technique for signals with time-varying periodicity. We show that for arbitrary variation of pitch periodicity in speech signal,the unwarping technique maps the signals to periodic signals which enable eficient estimation of periodicity. We demonstrate the e�ectiveness of the new technique using both synthetic and real speech signals.