STFLSTUDIO2/KIT 查看數據表（PDF） - STMicroelectronics
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STFLSTUDIO2/KIT Datasheet PDF : 28 Pages
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W.A.R.P.2.0
Table 3. Operating Modes (1)
Mode PRESET OFL AUTO OE I0-I7
RD SIS0-SIS2 O0-O7 O8-O10 O11 OC0-OC1
Off-Line
Slave
VIH
Off-Line
Autoboot
VIH
On-Line
M aster(2 )
VIH
On-Line
Slave(3)
VIH
VIH
VIL X Data In
X
X
X
X
X
Clock
VIH
VIH VIH Data In
X
Rate
Selection
External Memory
Addresses
X
Code
VIL
X(2) VIH Data In
(2)
X
Data
Out
Next
Input
Output
Selection
VIL
X(2) VIH Data In
Input
Data
Selection Out
X
(2)
Output
Selection
Output
Disable
VIH
X
X
VIL
X
X
X
Hi-Z
X
Reset(4)
X
X
X
X
X
X
VOL
VOL
VOL
VOL
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 WAIT pulses are optional.
4. Same operation is obtained when positive and negative OFL transactions occour.
INTERNAL STRUCTURE
The block diagram shown in figure 2 describes the
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
data routing. Data are read one byte a time from the
input data bus, internally stored, and sent to the
ALPHA calculator following the rules loaded in the
Program Memory. Input data resolution is 8 bit.
The cycle starts when all inputs or a LASTIN High
have been provided and continues until BUSY is
active or a PRESET signal is given. When BUSY
becomes inactive a new acquisition phase can start.
Alpha Calculator. This block calculates the inter-
section (ALPHA weight) between an Antecedent
Membership Function and the corresponding crisp
input (see figure 8).
Inference Unit. Thanks to the Theta Operator, the
Inference Unit generates the THETA weights which
are used to manipulate the consequent MFs.
This is a calculation of the maximum and/or mini-
mum performed on ALPHA values according to the
logical connectives of fuzzy rules. It is possible to
utilize the AND/OR connectives and to directly ex-
ploit ALPHA weights or the negated values. The
number of THETA weights depends on the number
of rules.
The rules can have at maximum four ALPHA
weights (however they are connected).Two or more
rules can be only joined with the OR connective.
Inference Unit structure is shown in figure 9.
Defuzzifier. It generates the output crisp values
implementing the consequent part of the rules.
In this method consequentMFs are multiplied by a
weight value Ω (OMEGA), which is calculated on
the basis of antecedent MFs and 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 modified by a rule weight.
Output value (Y) is deduced from the centroids (Xi)
and the modified MFs (Ωi ) by using the formula:
n
∑ Ωi ∗ Xi
Y= 1 n
∑ Ωi
1
n = number of MFs of the Output Variable.
Xi =absciss of the MFi centroid.
Ωi =membership degree of the output MFi.
Two parallel blocks calculate the numerator and
denominator values to implement the centroids
formula. A final division block calculates the output
values (see figure 10).
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