David A Giangano

Title: David A. Giangano: Innovator in Analog-to-Digital Conversion

Introduction

David A. Giangano is a notable inventor based in Elmhurst, NY (US). He has made significant contributions to the field of analog-to-digital conversion, holding a total of 3 patents. His work focuses on enhancing the accuracy and efficiency of signal processing technologies.

Latest Patents

One of Giangano's latest patents is the "Ultra Linear Spectroscopic Analog-to-Digital Converter." This invention employs a sliding scale averaging technique for an analog-to-digital converter. An analog signal is summed with a varying number prior to conversion, which minimizes errors due to unequal bin widths. The invention also includes a comparator technique to ensure that the summed signal does not exceed the full dynamic range of the ADC.

Another significant patent is the "Programmable Frequency Identifier Circuit." This circuit identifies the frequency of a contaminated signal and includes a digital finite impulse response filter, a zero-crossing detector, a zero-crossing counter, and a frequency range decoder. The programmable filter is designed to filter signals while the zero-crossing counter counts the sign changes occurring during a programmably determined frame time. This allows for precise identification of the desired frequency.

Career Highlights

David A. Giangano is currently employed at Grumman Aerospace Corporation, where he continues to innovate in the field of signal processing. His work has had a substantial impact on the development of advanced technologies in aerospace and other industries.

Collaborations

Throughout his career, Giangano has collaborated with talented individuals such as Cecelia Jankowski and Steven J. Bocskor. These collaborations have contributed to the advancement of his projects and innovations.

Conclusion

David A. Giangano is a distinguished inventor whose work in analog-to-digital conversion has led to significant advancements in technology. His patents reflect a commitment to improving the accuracy and efficiency of signal processing systems.