Embodiments described herein relate to a method for modifying transmission line characteristics. The method may include: making a first determination of a null frequency of an input signal to a transmission line; performing an analysis to make a second determination of a wavelength of the input signal using, at least in part, the null frequency; making a third determination, based on the analysis, of a half wavelength of the input signal; calculating, based on the half wavelength, a total stub length; and adding a trace to a stub associated with a via, wherein the stub and the trace are a length that is at least a portion of the half wavelength of the input signal.

Embodiments described herein relate to a method for modifying transmission line characteristics. The method may include: making a first determination of a null frequency of an input signal to a transmission line; performing an analysis to make a second determination of a wavelength of the input signal using, at least in part, the null frequency; making a third determination, based on the analysis, of a half wavelength of the input signal; calculating, based on the half wavelength, a total stub length; and adding a trace to a stub associated with a via, wherein the stub and the trace are a length that is at least a portion of the half wavelength of the input signal.

Disclosed are a method and an apparatus for improving circuit health. The method includes obtaining an S-parameter plot of a circuit having an input port and an output port; determining a resonance frequency of the circuit based on the S-parameter plot; and estimating the health of the circuit based on the resonance frequency.

Disclosed are a method and an apparatus for improving circuit health. The method includes obtaining an S-parameter plot of a circuit having an input port and an output port; determining a resonance frequency of the circuit based on the S-parameter plot; and estimating the health of the circuit based on the resonance frequency.

A method includes receiving electrical measurements of an input signal of a power system. The method includes determining an estimated frequency of the power system using a rate of change of phase of the power system and using zero crossings of the power system. Selection between using the rate of change of phase of the power system and using zero crossings of the power system is based on a comparison between an estimated phase angle and a measured phase angle of the power system.

A method includes receiving electrical measurements of an input signal of a power system. The method includes determining an estimated frequency of the power system using a rate of change of phase of the power system and using zero crossings of the power system. Selection between using the rate of change of phase of the power system and using zero crossings of the power system is based on a comparison between an estimated phase angle and a measured phase angle of the power system.

A frequency characteristic measurement apparatus includes a calibration circuit configured to perform a SOLT calibration on cable end surfaces, a first measurement circuit measuring S-parameters of a first substrate provided with a DUT, after the SOLT calibration by the calibration circuit, a second measurement circuit measuring S-parameters of a second substrate after the SOLT calibration by the calibration circuit, and an extraction circuit performing a vector operation of a measurement result of the first measurement circuit and a measurement result of the second measurement circuit to extract S-parameters of the DUT. The extraction circuit assumes that a reflection of each of first second fixtures obtained by virtually dividing the second substrate into two parts at the center, on an end surface of the second substrate is equal to or smaller than a reflection on an end surface of the second substrate without the virtual division at the center.

A frequency characteristic measurement apparatus includes a calibration circuit configured to perform a SOLT calibration on cable end surfaces, a first measurement circuit measuring S-parameters of a first substrate provided with a DUT, after the SOLT calibration by the calibration circuit, a second measurement circuit measuring S-parameters of a second substrate after the SOLT calibration by the calibration circuit, and an extraction circuit performing a vector operation of a measurement result of the first measurement circuit and a measurement result of the second measurement circuit to extract S-parameters of the DUT. The extraction circuit assumes that a reflection of each of first second fixtures obtained by virtually dividing the second substrate into two parts at the center, on an end surface of the second substrate is equal to or smaller than a reflection on an end surface of the second substrate without the virtual division at the center.

Systems and methods for estimating frequency and bandwidth of unknown signals using learned features of a filter pair for the purpose of detecting, separating and tracking these signals in an electronic receiver. The techniques could be part of a signal cueing system that initiates signal detection, separation and tracking or a signal separation and tracking system which is initialized by the cueing system and adaptively updates frequency and bandwidth estimates so as to continuously separate and track signals after initial detection. The methodology is to train the filter responses using machine learning by creating a grid of training data based on signal examples that cover a span of frequencies and bandwidths. The system estimates frequency and bandwidth in real time, inputs those estimates into interpolating lookup tables to retrieve filter coefficients, and provides those filter coefficients to a tunable tracking filter.

Systems and methods for estimating frequency and bandwidth of unknown signals using learned features of a filter pair for the purpose of detecting, separating and tracking these signals in an electronic receiver. The techniques could be part of a signal cueing system that initiates signal detection, separation and tracking or a signal separation and tracking system which is initialized by the cueing system and adaptively updates frequency and bandwidth estimates so as to continuously separate and track signals after initial detection. The methodology is to train the filter responses using machine learning by creating a grid of training data based on signal examples that cover a span of frequencies and bandwidths. The system estimates frequency and bandwidth in real time, inputs those estimates into interpolating lookup tables to retrieve filter coefficients, and provides those filter coefficients to a tunable tracking filter.