Loren R Eggert

USPTO Granted Patents = 15 (Patent Applications = 1)

Average Co-Inventor Count = 2.3

ph-index = 1

Forward Citations = 4(Granted Patents)

Location History:

San Jose, CA (US) (2021 - 2023)
Indianapolis, IN (US) (2013 - 2024)
Chandler, AZ (US) (2024)

Company Filing History:

Years Active: 2013-2025

Loading Chart...

15 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12218710 - Per-channel modulation error ratio (MER) calibration and determination on a multi channel receiver (2025-02-04),

2. 12034619 - Upstream signal leakage detection in high-split cable network (2024-07-09),

3. 11991414 - Method and apparatus providing out of band validation by content analysis in a cable TV network (2024-05-21),

4. 11677439 - Method and apparatus providing common path distortion (CPD) detection from a field instrument (2023-06-13),

5. 11665396 - Method and apparatus providing out of band validation by content analysis in a cable TV network (2023-05-30),

6. 11650266 - Systems and methods for detecting leakage in a cable network system (2023-05-16),

7. 11621884 - High resolution time domain reflectometry (TDR) in fault location measurement in a cable network (2023-04-04),

8. 11601717 - Method and apparatus providing optimized MPEG validation in a cable TV network (2023-03-07),

9. 11575468 - Methods and systems for determing stress on a low density parity check (LDPC) process for a network using orthogonal frequency division multiplexing (OFDM) (2023-02-07),

10. 11239924 - Per-channel modulation error ratio (MER) calibration and determination on a multi channel receiver (2022-02-01),

11. 11218189 - Method and apparatus providing common path distortion (CPD) detection from a field instrument (2022-01-04),

12. 11153650 - Method and apparatus providing optimized MPEG validation in a cable TV network (2021-10-19),

13. 11121807 - Methods and systems for determining stress on a low density parity check (LDPC) process for a network using orthogonal frequency division multiplexing (OFDM) (2021-09-14),

14. 11085973 - Systems and methods for detecting leakage in a cable network system (2021-08-10),

15. 8345737 - Detection of network impairments through tilt-normalized measurement data (2013-01-01),

Title: The Innovations of Loren R Eggert

Introduction

Loren R Eggert, based in Indianapolis, IN, is a distinguished inventor known for his significant contributions to the field of technology. With 15 patents to his name, he has made an impact through his innovative approaches and methodologies in signal processing and communication technologies.

Latest Patents

Among his latest inventions are two noteworthy patents. The first patent focuses on "Per-channel modulation error ratio (MER) calibration and determination on a multi-channel receiver." This invention outlines a method, apparatus, and system designed for the calibration and determination of MER in multi-channel receivers effectively. The second patent, titled "Upstream signal leakage detection in high-split cable network," describes a system where a Cable Modem Termination System (CMTS) may prompt cable modems to transmit a specific upstream test signal. Utilizing a leakage detection device, it filters and analyzes signals to identify potential leakage, enhancing the reliability of cable network transmissions.

Career Highlights

Loren has a reputable career with significant tenure at prominent companies such as Viavi Solutions Inc. and Acterna LLC. His work at these companies has been instrumental in advancing technology in telecommunications.

Collaborations

During his career, Loren has collaborated with esteemed colleagues, including Daniel Keith Chappell and Robert Flask, further enriching his innovative endeavors and expanding the scope of his projects.

Conclusion

Loren R Eggert stands as a testament to the spirit of innovation, making significant strides in technology through his patents and collaborative efforts. His inventions not only address current challenges in the industry but also pave the way for future advancements.

This text is generated by artificial intelligence and may not be accurate.

Please report any incorrect information to support@idiyas.com