W.A.R.P.1.1

Features: High Speed Rules ProcessingAntecedent Membership Functions with any Shape Up to 256 Rules (4 Antecedents,1 Consequent) Up to 16 Input ConfigurableVariables Up to 16 Membership Functions for an Input Variable Up to 16 OutputVariables Up to 128 Membership Functions for all Consequents MAX...

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W.A.R.P.1.1 Picture
SeekIC No. : 004544339 Detail

W.A.R.P.1.1: Features: High Speed Rules ProcessingAntecedent Membership Functions with any Shape Up to 256 Rules (4 Antecedents,1 Consequent) Up to 16 Input ConfigurableVariables Up to 16 Membership Functions f...

floor Price/Ceiling Price

Part Number:
W.A.R.P.1.1
Supply Ability:
5000

Price Break

  • Qty
  • 1~5000
  • Unit Price
  • Negotiable
  • Processing time
  • 15 Days
Total Cost: $ 0.00

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Month Sales

268 Transactions

Rating

evaluate  (4.8 stars)

Upload time: 2024/4/25

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Product Details

Description



Features:

High Speed Rules Processing
 Antecedent Membership Functions with any Shape
Up to 256 Rules (4 Antecedents,1 Consequent)
Up to 16 Input ConfigurableVariables
Up to 16 Membership Functions for an Input Variable
Up to 16 OutputVariables
Up to 128 Membership Functions for all Consequents
MAX-DOT Inference Method
Defuzzification on chip
Software Tools and Emulators Availability
100-pin CPGA100 Ceramic Package
84-lead Plastic Leaded Chip Carrier package



Specifications

Symbol

Parameter

Value

Unit

VDD

Supply Voltage

-0.5 to 7

V

VI

Input Voltage

-0.5 to VDD+0.5

V

VO

Ouput Voltage

-0.5 to VDD+0.5

V

IOL

Output Sink PeakCurrent

+24

mA

IOH

Output Source Peak Current

-12

mA

TOPT

Operating Temperature

0 to +70

°C

TSTG

Storage Temperature (Ceramic)

-65 to +150

°C

Storage Temperature (Plastic)

-45 to +125

°C




Description

W.A.R.P. is a VLSI Fuzzy Logic controller whose architecture arises from the need of realizing an integrated structure with high inferencing performances and flexibility. To get those results a modular architecture based on a set of parallel memory blocks has been implemented.

In orderto obtainhigh performancesW.A.R.P.uses different data representations during the various phases of the computational cycle, so that it is always operating on the optimal data representation. A vectorial characterization has been adopted for the Antecedent Membership Functions. W.A.R.P. exploits a SGS-THOMSON patented strategyto store theAntecedentMembership




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