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STFLAFM10 Scheda tecnica(PDF) 2 Page - STMicroelectronics |
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STFLAFM10 Scheda tecnica(HTML) 2 Page - STMicroelectronics |
2 / 4 page LEARNING it is composed by two phases: BUILDING RULES It allows to perform the auto- matic selection of inference rules or their manual definition, taking in to account the project con- strains read from the previously opened pattern file. As a result the user will be supplied with a rule file containing the linguistic expression of the rules. An unsupervised clustering algorithm is used to per- form this task. BUILDING MEMBERSHIP FUNCTIONS It allows the user to select the membership function shape and the fuzzy intference method for the project elaboration. Starting from the rule file supplied by the previous phase, it initially associates to each fuzzy set a standard membership function shape. These shapes can be gradually tuned in order to let the fuzzy system to better approximate the proc- ess/function sampling by means of subsequently run sessions. Back-propagation algorithm with automatic learning rate control is used to this aim. TOOLS It is composed of different sub-menus: LOCAL RULES it allows to add new rules to the fuzzy logic knowledge base determined by an Adaptive Fuzzy Modeller run session. Aim of this functionality is the local approximation level im- provement. SIMULATION it allows to simulate the fuzzy system behaviour in order to verify the approximation level obtained during the learning phase. The simulation can be carried out in two different ways. Simulation Step-by-Step: the user must supply the simulator with the values variables correspond- ing to the point to verify. Simulation from File: the user must supply the simulator with the name of a process/function stream file that will be used to perform a complete process inference. VIEW FEATURES View Features of the AFM gives with the capability to visualize the fuzzy model extracted for a particu- lar project. It allows a separate visualization of the rules of inference and membership functions. The rules can be visualized in a linguistic format. For the membership functions you can choose between a linguistic and a graphical format visualization. EXPORTERS The Exporter provides library functions working on the databases automatically generated, which appropriately describe the data structures of the selected project in terms of a different program- ming environment. These functions can be exploited inside the user’s programs in order to verify the model extracted and to use it in real application. SUPPORTED TARGETS The supported environment are: - W.A.R.P.1.1 using FUZZYSTUDIO ™1.0 - W.A.R.P.2.0 using FUZZYSTUDIO ™2.0 - MATLAB - C Language - Fu.L.L. (Fuzzy Logic Language). Learning Phases pattern file Fuzzy Logic knowledge base Simulation and Manual Tuning exporter to processor W.A.R.P. 1.1 W.A.R.P. 2.0 ANSI C MATLAB Rules extractor MFs tuning rules minimizer Figure 2. AFM Logic Flow. Figure 3. BUILD MEMBERSHIP FUNCTION window 2/4 ADAPTIVE FUZZY MODELLER 1.0 |
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