Ex Parte Chowdhury et al

Patent Trial and Appeal Board

Jan 16, 2013

11545440 (P.T.A.B. Jan. 16, 2013)

UNITED STATES PATENT AND TRADEMARK OFFICE
_____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
_____________

Ex parte ATISH DATTA CHOWDHURY, NAMIT CHATURVEDI,
MEENAKSHI BALASUBRAMANIAN, and ARUL GANESH
_____________

Appeal 2010-008359
Application 11/545,440
Technology Center 2100
______________

Before DAVID M. KOHUT, JOHNNY A. KUMAR, and
MICHAEL J. STRAUSS, Administrative Patent Judges.

KOHUT, Administrative Patent Judge.

DECISION ON APPEAL

Appeal 2010-008359
Application 11/545,440

2
This is a decision on appeal under 35 U.S.C. § 134(a) of the Final
Rejection of claims 1-28. We have jurisdiction under 35 U.S.C. § 6(b).
We affirm the Examiner’s rejection of these claims.

INVENTION
The invention is directed to a method, device, and system for
receiving an input and supplying an output through the use of a processor
and a finite state automaton. Spec. 4-5. Claim 1 is representative of the
invention and is reproduced below:
1. A small intelligent device comprising:
a memory storing a finite state automaton;
an input/output interface that receives an input and provides
an output;
a processor, wherein the processor is arranged to receive the
input and to traverse the finite state automaton stored in the
memory in order to supply the output to the input/output
interface.

REFERENCES
Arbuckle US 5,563,805 Oct. 8, 1996

Briel US 6,119,183 Sep. 12, 2000

Montgomery US 2001/0000814 A1 May 3, 2001

Xie US 2002/0013934 A1 Jan. 31, 2002

Reggiani US 2003/0066021 A1 Apr. 3, 2003

Sidle US 2005/0278669 A1 Dec. 15, 2005

Bear US 2006/0032905 A1 Feb. 16, 2006

Appeal 2010-008359
Application 11/545,440

3
Gould US 7,082,044 B2 July 25, 2006

Arlindo L. Oliveira, et al., "Exact Minimization of Binary Decision
Diagrams Using Implicit Techniques," IEEE Transactions on
Computers, Vol. 47, No. 11, November 1998. (Hereinafter referred to
as Oliveira.)

Ronald M. Kaplan, "Finite State Technology," Xerox Palo Alto
Research Center, September 9, 1999. (Hereinafter referred to as
Kaplan.)

C. Enrique Ortiz, "An Introduction to Java Card Technology - Part 1,"
May 29, 2003. (Hereinafter referred to as Ortiz.)

“Smart Cards” by Cornerstone Lab, from www.c-
lab.com/smartCard.html. posted on the internet on January 25, 2005.
(Hereinafter referred to as C-Lab.)

Tor Helleseth et al., “Security of Jump Controlled Sequence
Generators for Stream Ciphers,” SETA 2006, LNCS 4086, pp. 141-
152, September 21, 2006. (Hereinafter referred to as Helleseth.)

REJECTIONS AT ISSUE
Claims 1, 3, 7, and 17 are rejected under 35 U.S.C. § 102(b) as being
anticipated by Montgomery. Ans. 4-5.
Claim 2 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Sidle. Ans. 6.
Claims 4-5 are rejected under 35 U.S.C. § 103(a) as being
unpatentable over the combination of Montgomery, Kaplan, and Arbuckle.
Ans. 6-8.
Claim 6 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery, Kaplan, and Sidle. Ans. 9-11.
Appeal 2010-008359
Application 11/545,440

4
Claims 8-12 are rejected under 35 U.S.C. § 103(a) as being
unpatentable over the combination of Montgomery and Ortiz. Ans. 11-14.
Claim 13 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Briel. Ans. 14-15.
Claim 14 rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery, Reggiani, and Helleseth. Ans. 15-17.
Claim 15 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Xie. Ans. 17-18.
Claims 16 and 18-20 are rejected under 35 U.S.C. § 103(a) as being
unpatentable over the combination of Montgomery and C-Lab. Ans. 18.
Claim 21 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Kaplan. Ans. 18-20.
Claim 22 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Bear. Ans. 20-21.
Claim 23 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery, Bear, and Sidle. Ans. 22.
Claims 24-26 are rejected under 35 U.S.C. § 103(a) as being
unpatentable over the combination of Montgomery and Oliveira. Ans. 23-
25.
Claim 27 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery, Sidle, and Oliveira. Ans. 25.
Claim 28 is rejected under 35 U.S.C. § 103(a) as being unpatentable
over the combination of Montgomery and Gould. Ans. 25-26.

Appeal 2010-008359
Application 11/545,440

5
ISSUES
Did the Examiner err in finding that Montgomery discloses a small
intelligent device having a memory that stores a finite state automaton, as
required by claim 1?
Did the Examiner err in finding that it would have been obvious to
combine Montgomery and Sidle?
Did the Examiner err in finding that the combination of Montgomery,
Kaplan, and Arbuckle teaches or suggests a finite state automaton that
embodies application context sensitive and application context independent
rules, as required by claim 4?
Did the Examiner err in finding that the combination of Montgomery
and Briel teaches or suggests a finite state automaton that is stored as a
switching circuit representation, as required by claim 13?
Did the Examiner err in finding that the combination of Montgomery
and Kaplan teaches or suggests a data structure that transitions the finite
state automaton from an initial state to a next state in response to an input, as
required by claim 21?
Did the Examiner err in finding that the combination of Montgomery
and Oliveira teaches or suggests: a finite state automaton in the form of a
decision tree in the memory of a small intelligent device, as required by
claim 24; a decision tree that comprises a binary decision tree, as required by
claim 25; and level indicators, as required in claims 26 and 27?
Did the Examiner err in finding that the combination of Montgomery
and Gould teaches or suggests wherein the finite state automaton comprises
accepting states and non-accepting states, wherein the processor transitions
to a new state, wherein the input is an allowable sequence if the new state
Appeal 2010-008359
Application 11/545,440

6
comprises an accepting state, and wherein the input is not an allowable
sequence if the new state comprises a non-accepting state, as required by
claim 28?
ANALYSIS
Claims 1, 3, 7, and 17.
We select claim 1 as representative of the group comprising claims 1,
3, 7, and 17 as Appellants have not addressed any of the other claims with
particularity. 37 C.F.R. § 41.37(c)(1)(vii). Appellants argue that
“Montgomery does not disclose a small intelligent device having a memory
that stores a finite state automaton,” as required by claim 1. App. Br. 17.
Specifically, Appellants argue that Montgomery discloses software and
programs stored on the smart card and a processor for carrying out
operations, but do not mention storing a finite state automaton. App. Br. 18.
Instead, Appellants argue that even though Montgomery describes the
operation of the smart card using a state diagram, Montgomery never
mentions storing a finite state automaton on the smart card. App. Br. 18.
We disagree.
The Examiner finds that Montgomery’s smart card processor executes
programs that are stored in its memory. Ans. 28. The Examiner additionally
finds that Montgomery’s Figures show the smart card operating as a finite
state machine. Ans. 28. Therefore, the Examiner finds that a finite state
automaton is stored in Montgomery’s memory of the smart card. Ans. 28.
We agree with the Examiner’s findings and logic and subsequently sustain
the Examiner’s rejection of claims 1, 3, 7, and 17.
Appeal 2010-008359
Application 11/545,440

7
Claim 2
Appellants make the same arguments with respect to claim 2 as with
claim 1. App. Br. 20-21. Therefore, we sustain the Examiner’s rejection of
claim 2 for the same reasons indicated supra. However, Appellants also
argue that the combination of Montgomery and Sidle is improper since there
is no motivation to combine the two references. App. Br. 22. We disagree.
The Supreme Court stated that an explicitly stated motivation to
combine the references is seen as “helpful insight,” KSR Intern. Co. v.
Teleflex Inc., 550 U.S. 398, 418, but that the combination of familiar
elements according to known methods is likely to be obvious when it does
no more than yield predictable results. Id. at 416. In this situation, the
Examiner finds that Montgomery discloses a finite state automaton. Ans. 4.
Additionally, the Examiner finds that Sidle teaches a finite state machine
that corresponds to a binary decision diagram. Ans. 6. Both of the
references deal with state machines. Therefore, we consider using Sidle’s
binary decision diagrams of its finite state machines with Montgomery’s
finite state automaton as nothing more than using known elements according
to known methods in order to yield the predictable results.
Further, though explicit motivation to combine the references is not
required (see KSR, supra), the Examiner has provided a motivation to
combine them. The Examiner stated that the combination would provide “a
convenient means of finding the output of one or more functions for any
given input.” Ans. 6. While Appellants are correct that there is no
motivation explicitly cited by the references (App. Br. 22), we are not
persuaded that the motivation would not be known to one skilled in the art
(App. Br. 22) as indicated by the Examiner’s citation to Akers. Ans. 30.
Appeal 2010-008359
Application 11/545,440

8
Thus, we are not persuaded by Appellants’ arguments and we sustain
the Examiner’s rejection of claim 2.
Claim 4.
Appellants make the same arguments with respect to claim 4 as with
claim 1. App. Br. 24. We do not find those arguments to be persuasive for
the reasons discussed supra. Appellants additionally argue that Arbuckle
does not teach or suggest a finite state automaton that embodies application
context sensitive and application context independent rules, as required by
claim 4. App. Br. 25. However, as correctly indicated by the Examiner, the
Examiner finds that Kaplan teaches context sensitive and context
independent rules and Arbuckle teaches application contexts. Ans. 32-33.
Thus, the Examiner finds that it is the combination of Kaplan and Arbuckle
that teaches the disputed limitation. Ans. 32-33. Appellants do not address
the Examiner’s specific finding regarding the combination. Therefore, we
agree with the Examiner and sustain the Examiner’s rejection of claim 4.
Claims 5, 6, 8-12, 14-16, and 18-20.
Appellants make the same arguments with respect to claims 5, 6, 8-12,
14-16, and 18-20 as with respect to claim 1. App. Br. 26-29. As such, we
sustain the Examiner’s rejection of claims 5, 6, 8-12, 14-16, and 18-20 for
the same reasons as discussed supra with respect to claim 1.
Claim 13.
Appellants make the same arguments with respect to claim 13 as with
claim 1. App. Br. 27. We do not find those arguments to be persuasive for
the reasons discussed supra. Appellants additionally argue that the
combination of Montgomery and Briel does not teach or suggest storing a
finite state automaton as a switching circuit representation because Briel
Appeal 2010-008359
Application 11/545,440

9
teaches implementing a switching circuit as a state machine, but not the
reverse. App. Br. 27. Appellants contend that the Examiner’s finding that
Briel teaches the disputed limitation is only logical “when all finite state
machines can be implemented as switching circuits.” App. Br. 27.
However, we agree with the Examiner that it would have been obvious to
one of ordinary skill in the art to create a state machine based on a switching
circuit since it is known to create a switching circuit based on a state
machine. Ans. 36. Thus, we sustain the Examiner’s rejection of claim 13.
Claim 21.
Appellants make the same arguments with respect to claim 21 as with
claim 1. App. Br. 29-30. We do not find those arguments to be persuasive
for the reasons discussed supra. Appellants additionally argue that neither
Montgomery nor Kaplan teaches or suggests a data structure that transitions
the finite state automaton from an initial state to a next state in response to
an input, as required by claim 21. App. Br. 31. Appellants contend that the
Figures and sections of Montgomery cited by the Examiner do not discuss a
transition between states in response to an input. App. Br. 31. However, the
Examiner finds that Montgomery teaches a smart card that waits for a
command (ST21), i.e., an initial state. Ans. 38. Upon receipt of a
command, the Examiner finds that the smart card enters a “next state.” Ans.
38. Additionally, the Examiner finds that Kaplan teaches an initial state and
the transitions from state to state as inputs are received. Ans. 38. We find
the Examiner’s findings to be reasonable and Appellants have not addressed
the Examiner’s specific findings. As such, we sustain the Examiner’s
rejection of claim 21.
Appeal 2010-008359
Application 11/545,440

10
Claim 22.
Appellants make the same arguments with respect to claim 22 as with
claim 1, in respect to Montgomery. App. Br. 32. We do not find those
arguments to be persuasive for the reasons discussed supra. Claim 22
recites “wherein the reader memory stores an execution logic of the finite
state automaton.” Appellants argue that Bear does not teach or suggest this
limitation because there is nothing in the reference that includes storing
execution logic in memory. App. Br. 32. However, the Examiner finds that
Bear discloses ROM, and as such, it would have been obvious to include
execution logic in the ROM of Bear in order “to provide a means for
accomplishing the state machines of Montgomery’s figures without having
to involve the terminal.” Ans. 30. We agree with the Examiner’s rationale
and Appellants have not addressed the Examiner’s specific finding. Thus,
we sustain the Examiner’s rejection of claim 22.
Claims 24 and 25.
Appellants make the same arguments with respect to claims 24 and 25
as with claim 1. App. Br. 34. We do not find those arguments to be
persuasive for the reasons discussed supra. Appellants argue that neither
Montgomery nor Oliveira teaches or suggests a finite state automaton in the
form of a decision tree, as required by claim 24, or wherein the decision tree
is a binary decision tree, as required by claim 25. App. Br. 34. Appellants
are not arguing that decision trees are not taught; just that it would not have
been obvious to store a finite state automaton as a decision tree. App. Br.
34. We disagree.
The Examiner finds that Oliveira teaches a binary decision diagram in
Figure 3. Ans. 23. Additionally, the Examiner finds that it would have been
Appeal 2010-008359
Application 11/545,440

11
obvious to combine Montgomery with Oliveira in order to minimize the
decision diagram for optimization purposes (citing Oliveira’s Abstract).
Ans. 23. We find this motivation to be reasonable and Appellants have not
addressed the Examiner’s specific finding. Thus, we sustain the Examiner’s
rejection of claims 24 and 25.
Claims 26 and 27.
Appellants make the same arguments with respect to claims 26 and 27
as with claim 1. App. Br. 34-36. We do not find those arguments to be
persuasive for the reasons discussed supra. Appellants additionally argue
that none of the cited references teaches or suggests level indicators that
have a first value indicating that a corresponding node maps to a state of the
automaton and a second value that indexes an input string, as required by
claim 26. App. Br. 35-36. Appellants contend that the values indicated by
the Examiner (X1, X2, and X3), could represent anything because Oliveira
does not describe their function. App. Br. 35-36. Appellants also argue that
since the levels are not taught by the references, that the references also do
not teach a first value and a second value as described in the claims. We
disagree.
The Examiner finds that X1, X2, and X3 are levels in Figure 3’s
decision tree. Ans. 42. After reviewing Figure 3 of Oliveira, we agree with
the Examiner that X1, X2, and X3 represent different levels of a decision
tree. Additionally, the Examiner finds that Oliveira teaches minterms and
values of the minterms and the level of the node in the binary decision
diagram relates to the index of the variable that is tested at that node. Ans.
42. Appellants do not address the Examiner’s specific findings. Thus, we
Appeal 2010-008359
Application 11/545,440

12
agree with the Examiner and sustain the Examiner’s rejection of claims 26
and 27.
Claim 28.
Appellants make the same arguments with respect to claim 28 as with
claim 1. App. Br. 36-37. We do not find those arguments to be persuasive
for the reasons discussed supra. Appellants additionally argue that the
combination of Montgomery and Gould does not teach or suggest wherein
the finite state automaton comprises accepting states and non-accepting
states, wherein the processor transitions to a new state, wherein the input is
an allowable sequence if the new state comprises an accepting state, and
wherein the input is not an allowable sequence if the new state comprises a
non-accepting state, as required by claim 28. App. Br. 37. We disagree.
The Examiner finds that Gould teaches “a finite state machine,
transitioning between states, and an accepting state.” Ans. 44. Additionally,
the Examiner finds that claim 8 of Gould teaches using a look-up table
(LUT) to generate an output after receiving a next state, and accepting or
rejecting a request. Ans. 44. Thus, we agree with the Examiner that the
disputed limitations are taught. Additionally, Appellants do not address the
Examiner’s specific findings regarding claim 8 of Gould nor do Appellants
provide sufficient evidence or reasoning to show why the portions of Gould
cited by the Examiner do not teach the disputed claim limitation. As such,
we sustain the Examiner’s rejection of claim 28.
Appeal 2010-008359
Application 11/545,440

13
CONCLUSION
The Examiner did not err in finding that Montgomery discloses a
small intelligent device having a memory that stores a finite state automaton,
as required by claim 1.
The Examiner did not err in finding that it would have been obvious
to combine Montgomery and Sidle.
The Examiner did not err in finding that the combination of
Montgomery, Kaplan, and Arbuckle teaches or suggests a finite state
automaton that embodies application context sensitive and application
context independent rules, as required by claim 4.
The Examiner did not err in finding that the combination of
Montgomery and Briel teaches or suggests a finite state automaton that is
stored as a switching circuit representation, as required by claim 13.
The Examiner did not err in finding that the combination of
Montgomery and Kaplan teaches or suggests a data structure that transitions
the finite state automaton from an initial state to a next state in response to
an input, as required by claim 21.
The Examiner did not err in finding that the combination of
Montgomery and Oliveira teaches or suggests: a finite state automaton in the
form of a decision tree in the memory of a small intelligent device, as
required by claim 24; a decision tree that comprises a binary decision tree, as
required by claim 25; and level indicators, as required in claims 26 and 27.
The Examiner did not err in finding that the combination of
Montgomery and Gould teaches or suggests wherein the finite state
automaton comprises accepting states and non-accepting states, wherein the
processor transitions to a new state, wherein the input is an allowable
Appeal 2010-008359
Application 11/545,440

14
sequence if the new state comprises an accepting state, and wherein the input
is not an allowable sequence if the new state comprises a non-accepting
state, as required by claim 28.

SUMMARY
The Examiner’s decision to reject claims 1-28 is affirmed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED

ELD