Laurel, MD, United States of America

Garth S Barbour


Average Co-Inventor Count = 4.0

ph-index = 2

Forward Citations = 93(Granted Patents)


Company Filing History:


Years Active: 1996-1998

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2 patents (USPTO):Explore Patents

Title: Innovations of Garth S Barbour in Neural Network Systems

Introduction

Garth S Barbour, an innovative inventor based in Laurel, MD, is recognized for his contributions to the field of neural networks. With a total of two patents to his name, Barbour has made significant strides in developing systems that enhance our understanding of associative learning through advanced neural network architectures.

Latest Patents

One of Garth S Barbour's notable patents is titled "Dynamically Stable Associative Learning Neural Network System". This invention introduces a unique architectural unit comprising conditioned and unconditioned signal inputs along with an output. The system features 'patches,' which serve as storage areas for dynamic interactions between the input signals, allowing for local processing to achieve associative learning. These patches can be adjusted in size through methods known as 'pruning' or 'budding'. The neural network is trained by methodically applying input signal sets until dynamic equilibrium is established. The enhancements of the basic unit lead to multilayered systems, significantly increasing capabilities in complex pattern classification and feature recognition.

Career Highlights

Throughout his career, Garth S Barbour has contributed to various organizations, including the United States of America as represented by the Secretary of the Army, and Erim International, Inc. His work in these institutions has been pivotal in advancing research and applications of neural networks.

Collaborations

Garth has collaborated with esteemed colleagues such as Daniel L Alkon and Thomas P Vogl, exchanging ideas and expertise that have fueled advancements in their respective fields. These collaborations underscore the importance of teamwork and synergy in the realm of innovation.

Conclusion

Garth S Barbour's inventive spirit continues to push the boundaries of what is possible within neural network systems. His work not only contributes to the theoretical framework of associative learning but also opens doors for practical applications in various industries. As the field evolves, Barbour's inventions remain a testament to the power of innovation and creativity in shaping our understanding of complex systems.

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