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STFLSTUDIO2KIT中文資料意法半導(dǎo)體數(shù)據(jù)手冊(cè)PDF規(guī)格書

廠商型號(hào) |
STFLSTUDIO2KIT |
功能描述 | ADAPTIVE FUZZY MODELLER |
文件大小 |
89.89 Kbytes |
頁面數(shù)量 |
4 頁 |
生產(chǎn)廠商 | STMicroelectronics |
企業(yè)簡(jiǎn)稱 |
STMICROELECTRONICS【意法半導(dǎo)體】 |
中文名稱 | 意法半導(dǎo)體集團(tuán)官網(wǎng) |
原廠標(biāo)識(shí) | ![]() |
數(shù)據(jù)手冊(cè) | |
更新時(shí)間 | 2025-6-26 17:25:00 |
人工找貨 | STFLSTUDIO2KIT價(jià)格和庫(kù)存,歡迎聯(lián)系客服免費(fèi)人工找貨 |
STFLSTUDIO2KIT規(guī)格書詳情
DESCRIPTION
Adaptive Fuzzy Modeller (AFM) is a tool that easily allows to obtain a model of a system based on Fuzzy Logic data structure, starting from the sampling of a process/function expressed in terms of InputOutput values pairs (patterns).
Its primary capability is the automatic generation of a database containing the inference rules and the parameters describing the membership functions.
The generated Fuzzy Logic knowledge base represents an optimized approximation of the process/function provided as input.
The AFM has the capability to translate its project files to FUZZYSTUDIO? project files, MATLAB and C code, in order to use this environment as a support for simulation and control .
The block diagram in fig.2 illustrates the AFM logic flow.
■ Up to 8 Input Variables and 4 Output Variables
■ Up to 8 Fuzzy Sets for each Input Variables
■ Up to 21?Fuzzy Rules
■ Rules Learning Phase using an unsupervised WTA-FAM
■ Membership Functions Learning Phase using a supervised BACK-FAM
■ Automatic and Manual Learning Rate
■ Rules Minimizer
■ Gaussian and Triangular Membership Functions Shape
■ Inference method based on Product or Minimum
■ Step-by-Step and from File Simulation available
■ Supported Target: W.A.R.P. 1.1, W.A.R.P. 2.0, MATLAB and ANSI C
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FREESCALE |
ROHS+Original |
NA |
407 |
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詢價(jià) | ||
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詢價(jià) | ||
FREESCALE |
23+ |
NA |
407 |
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詢價(jià) | ||
FREESCALE/飛思卡爾 |
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3000 |
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25+ |
QFN |
880000 |
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詢價(jià) | ||
FREESCALE |
QFN |
56520 |
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詢價(jià) | |||
FREESCALE |
24+ |
SMD |
20000 |
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詢價(jià) | ||
AIGMATE |
25+23+ |
QFN |
48146 |
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08+ |
QFN32 |
35 |
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詢價(jià) |