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參數(shù)資料
| 型號(hào)： | W.A.R.P.1.1 |
| 英文描述： | WEIGHT ASSOCIATIVE RULE PROCESSOR |
| 中文描述： | 重量的聯(lián)想規(guī)則處理器 |
| 文件頁數(shù)： | 8/28頁 |
| 文件大?。?/td> | 275K |
| 代理商： | W.A.R.P.1.1 |
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Mode
PRESET
OFL
AUTO
OE
I0-I7
RD
SIS0-SIS2
O0-O7 O8-O10
O11
OC0-OC1
Off-Line
Slave
V
IH
V
IH
V
IL
X
Data In
X
X
X
X
X
Off-Line
Autoboot
V
IH
V
IH
V
IH
V
IH
Data In
X
Clock
Rate
Selection
Code
External Memory
Addresses
X
On-Line
Master
(2)
V
IH
V
IL
X
(2)
V
IH
Data In
X
Data
Out
Next
Input
(2)
Output
Selection
On-Line
Slave
(3)
V
IH
V
IL
X
(2)
V
IH
Data In
Input
Selection
Data
Out
X
(2)
Output
Selection
Output
Disable
V
IH
X
X
V
IL
X
X
X
Hi-Z
X
Reset
(4)
X
X
X
X
X
X
V
OL
V
OL
V
OL
V
OL
Table 3. OperatingModes (1)
Notes: 1. This table uses default active handshaking signal polarity (see table 6), X =don’t care.
2. If AUTO is High pulse in O11 is absent.
3. LASTIN and WAITpulses are optional.
4. Same operation is obtained when positive and negative OFL transactions occour.
INTERNAL STRUCTURE
The blockdiagram shown in figure 2 describesthe
structure of W.A.R.P.2.0 (a more detailed block
diagram is shown in fig. 11).
Input Port
. This internal block performs the input
datarouting.Dataareread onebyteatimefromthe
input data bus, internally stored, and sent to the
ALPHA calculator following the rules loaded in the
ProgramMemory. Input data resolutionis 8 bit.
The cycle starts when all inputs or a LASTINHigh
have been provided and continues until BUSY is
active or a PRESET signal is given. When BUSY
becomesinactiveanewacquisitionphasecanstart.
Alpha Calculator.
This block calculates the inter-
section (ALPHA weight) between an Antecedent
Membership Functionand the correspondingcrisp
input (see figure 8).
Inference Unit
. Thanksto the Theta Operator,the
InferenceUnit generatesthe THETAweights which
are used to manipulatethe consequentMFs.
This is a calculation of the maximum and/or mini-
mum performedon ALPHAvaluesaccording to the
logical connectives of fuzzy rules. It is possible to
utilize the AND/OR connectivesand to directly ex-
ploit ALPHA weights or the negated values. The
number of THETA weights depends onthe number
ofrules.
The rules can have at maximum four ALPHA
weights(howevertheyareconnected).Twoormore
rules can be only joined with the OR connective.
InferenceUnit structure is shown in figure 9.
Defuzzifier
. It generates the output crisp values
implementing the consequentpart of the rules.
In thismethod consequentMFs are multiplied by a
weight value
(OMEGA
)
, which is calculated on
the basis of antecedentMFsand logical operators.
The processing of fuzzy rules produces, for each
output variable, a resulting membership function.
Each MF related to the processed output variable
is firstly modifiedby arule weight.
Output value (Y) is deducedfrom the centroids(X
i
)
and the modified MFs (
i
) byusing the formula:
Y
=
∑
1
n
i
X
i
∑
1
n
i
n = number of MFs of the Output Variable.
X
i
=absciss ofthe MF
i
centroid.
i
=membershipdegree of the output MF
i
.
Two parallel blocks calculate the numerator and
denominator values to implement the centroids
formula. Afinaldivision blockcalculates the output
values (see figure 10).
8/28
W.A.R.P.2.0
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