Neural Networks: Here, There, and Everywhere-An Examination of Available Intellectual Property Protection for Neural Networks in Europe and the United States

By Rao, Dana S | The George Washington Journal of International Law and Economics, January 1, 1996 | Go to article overview

Neural Networks: Here, There, and Everywhere-An Examination of Available Intellectual Property Protection for Neural Networks in Europe and the United States


Rao, Dana S, The George Washington Journal of International Law and Economics


1. Introduction

The development of neural networks, engineering constructs that simulate human neural interconnections,l has expanded rapidly in recent years.2 A neural network's structure allows it to "learn" information while training for a particular application.3 The network then can generalize the information to solve new problems outside the scope of its initial training.4 Neural networks differ from other forms of "artificial intelligence," such as expert systems and fuzzy logic, in that those technologies use a rules-based decision-making process and have no ability to learn.5 The U.S. Patent and Trademark Office (PTO) recognizes this difference and places "artificial intelligence" in a separate category.6 The particular characteristics of a neural network distinguish it from all other existing technologies and, thus, present unique intellectual property issues.

Neural network uses include credit fraud checking, signal/image processing, speech recognition, medical image analysis, and target recognition.7 As neural networks gain popularity and their use expands, more questions will arise concerning the scope and nature of their intellectual property protections. This Note discusses the problems involved in protecting neural network technology in the United States and the European Community (EC or Community) .

Specifically, this Note first examines the patentability of both hardware- and software-implemented neural networks in the United States. Second, the Note reviews the application of U.S. copyright law to hardware- and software-implemented neural networks. Third, the Note explores copyright and patent protections for neural networks under European law. The analysis section of this Note focuses on how much inventiveness U.S. and European law requires to allow intellectual property protection and how those standards apply to the neural network's "final weights."8

Neural networks can be implemented as software or hardware.9 Software networks solve different types of problems by varying the parameters required by the program.lo Hardware networks work for only a single application" but function more quickly than software networks.l2 Neural networks often need the extra speed because they conduct a large number of computations.l3 This Note will examine whether U.S. patent law applies to software-implemented neural networks in light of recent decisions by the U.S. Court of Appeals for the Federal Circuit.l4 The Note will then analyze whether software networks can receive patent protection in the EC, based on Trade Related Intellectual Property Side (TRIPS) agreements and the Berne Convention, EC directives, MemberState statutes, and Member-State case law.l5

Finally, this Note recommends that the United States protect this emerging technology by amending international agreements to cover neural networks and computer-generated works, and changing domestic law to match international protections, thereby ent worldwide. ing uniform treatment worldwide.

II. DISCUSSION

A. What are Neural Networks?

The neural network engineering architecture creates more flexible and adaptable intelligence systems by mimicking the structure of the human brain.l6 The human brain is estimated to consist of over 100 billion interconnected neurons.17 These neurons have three parts: the main cell body; the dendrite, which receives input to the neuron; and the axon, which transmits the output of the neuron.ls A synapse connects the axon of one neuron to the dendrite of a neighboring neuron.19 The neuron collects exciting and inhibiting signals at its synapses, compares them, and then acts depending on which signal dominates.20

In a neural network, perceptrons duplicate the functions of the neuron.21 Perceptrons consist of sensory units, associator units, and response units.22 The sensory units receive the input of the perceptron, the associators compare the exciting and inhibiting signals, and the response units transmit the output, if any. …

The rest of this article is only available to active members of Questia

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
One moment ...
Default project is now your active project.
Project items
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA 8, MLA 7, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Note: primary sources have slightly different requirements for citation. Please see these guidelines for more information.

Cited article

Neural Networks: Here, There, and Everywhere-An Examination of Available Intellectual Property Protection for Neural Networks in Europe and the United States
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

Help
Full screen
Items saved from this article
  • Highlights & Notes
  • Citations
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA 8, MLA 7, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    Thanks for trying Questia!

    Please continue trying out our research tools, but please note, full functionality is available only to our active members.

    Your work will be lost once you leave this Web page.

    Buy instant access to save your work.

    Already a member? Log in now.

    Search by... Author
    Show... All Results Primary Sources Peer-reviewed

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.