Mode

PRESET

OFL

AUTO

OE

I0-I7

RD

SIS0-SIS2

O0-O7 O8-O10

O11

OC0-OC1

Off-Line

Slave

X

Data In

X

X

X

X

X

Off-Line

Autoboot

Data In

X

Clock

Rate

Selection

Code

External Memory

Addresses

X

On-Line

Master

(2 )

X

(2)

Data In

X

Data

Out

Next

Input

(2)

Output

Selection

On-Line

Slave

(3)

X

(2)

Data In

Input

Selection

Data

Out

X

(2)

Output

Selection

Output

Disable

XX

X

X

X

Hi-Z

X

Reset

(4)

XX

X

X

X

X

Table 3. Operating Modes (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 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 consequent MFs 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.

and the modified MFs (

Y

=

∑

1

n

∑

1

n

n = number of MFs of the Output Variable.

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).

8/28

W.A.R.P.2.0