2. Attrasoft Component-Object Structures2.1 Neural Network Layer
2.2 Presentation Layer
2.3 Application Layer2.3.1 ABM 2.72.4 What is PolyApplet Class Library?
2.3.2 PolyNet 4.0
2.3.3 DecisionMaker 2.5
2.3.4 Predictor 2.6
2.5 Organization Of This User�s Guide
2.6 Terminology
2.7 Chapter Overview
2. Attrasoft Component-Object Structures
Attrasoft Component-Object structure consists of three layers:
Application Layer
Presentation Layer
Neural Network LayerThis software will use the following software to illustrate the Attrasoft objects structure:
ABM 2.7
DecisionMaker 2.5
Predictor 2.6
PolyNet 4.0There are two neural net modules:
ABM (Attrasoft Boltzmann Machine): binary "Boltzmann Machine" and "Hopfield Model ";
PolyNet: multi-valued "Boltzmann Machine" and "Hopfield Model ".The Attrasoft PolyNet simulates neurons with 16-bit integer values, while the ABM simulates binary neurons.
The library is called:
Attrasoft.PolyApplet63And the main class is:Attrasoft.PolyApplet63.PolyApplet63.There are two types of data used by neural network systems: user data or application data, and neural data. Neural networks use neural data. User data depends on the applications.
Examples of functions in this layer are:
This software will focus on numerical data. The Presentation (Translation) layer class library is:
- Images to neural data;
- Numerical data to neural data;
- Video data to neural data;
- �
Attrasoft.PolyApplet63.abm2And the main class is:Attrasoft.PolyApplet63.abm2.abm2Main.This is the front-end graphical user interface, which the users see directly.
ABM 2.7 has two layers:
Application Layer: ABM 2.7The presentation layer is absent and the user provides neural data directly to the PolyApplet63 component.
Neural Network Layer: PolyApplet63 (binary neurons)Attrasoft PolyNet has two layers:
Application Layer: PolyNet 4.0The presentation layer is absent and the user provides neural data directly to the PolyApplet63 component.
Neural Network Layer: PolyApplet63 (multi-valued neurons)The Attrasoft DecisionMaker has three layers:
Application Layer: DecisionMaker 2.52.3.4 Predictor 2.6
Presentation Layer: Abm2
Neural Network Layer: PolyApplet63 (binary neurons)The Attrasoft Predictor has three layers:
Application Layer: Predictor 2.62.4 What is PolyApplet Class Library?
Presentation Layer: Abm2
Neural Network Layer: PolyApplet63 (binary neurons)The Attrasoft PolyApplet class library has three parts:
This class library implements Attrasoft Component-Object structure, which consists of three layers:
- PolyApplet63 (�binary neurons� + �multi-valued neurons�)
- Abm2
- Predictor63, DecisionMaker63, PredictorPoly63, DecisionMakerPoly63
Application LayerPolyApplet63 is the Neural Network Layer class library. This library is further divided into two parts:
Presentation Layer
Neural Network LayerAbm2 is the Presentation Layer class library.
- Binary neurons
- Multi-valued neurons
The Application Layer class libraries are:
- Predictor63
- DecisionMaker63
- PredictorPoly63
- DecisionMakerPoly63.
2.5 Organization Of This User�s GuideThis class library is organized in three parts:
Neural Network LayerPart I, Neural Network Layer, consists of chapters, 3, 4, 5, 6, and 7.
Presentation Layer
Application Layer
Part II, Presentation Layer, consists of chapters 8, 9, 10, and 11.
Part III, Layer, Application consists of chapters 12, 13, 14, and 15.Predictor
Predictor refers to the standalone software, Attrasoft Predictor For Windows, 2.6.DecisionMakerDecisionMaker refers to standalone software, Attrasoft DecisionMaker for Windows, 2.5.ABMABM refers to standalone software, Attrasoft ABM for Windows, 2.7.PolyNetPolyNet refers to standalone software, Attrasoft PolyNet for Windows, 4.0.ImageFinderImageFinder refers to standalone software, Attrasoft ImageFinder for Windows, 6.0.
PolyAppletPolyApplet refers to class library, Attrasoft PolyApplet, 6.0. This class library is consists of:
PolyApplet63
- PolyApplet63 (abm + polynet)
- Abm2
- Predictor63
- DecisionMaker63
- PredictorPoly63
- DecisionMakerPoly63
PolyApplet63 refers to the Neural Layer component of the class library, Attrasoft PolyApplet, 6.0. This class library is consists two parts of:
Abm2
- Binary neurons
- Multi-valued neurons
Abm2 refers to the Presentation Layer component of the class library, Attrasoft PolyApplet, 6.0.
DecisionMaker63DecisionMaker63 refers to the Application Layer component of the class library, Attrasoft PolyApplet, 6.0.
Predictor63Predictor63 refers to the Application Layer component of the class library, Attrasoft PolyApplet, 6.0.
DecisionMakerPoly63DecisionMakerPoly63 refers to the Application Layer component of the class library, Attrasoft PolyApplet, 6.0.
PredictorPoly63PredictorPoly63 refers to the Application Layer component of the class library, Attrasoft PolyApplet, 6.0.
Abm63The neural network layer class library is PolyApplet63. This class library has two groups of commands, with one group dealing with binary neural net and the other group dealing with multi-valued neural net. Abm63 refers to a component of the class library, PolyApplet63, which deals with the binary commands.
PolyNet63The neural network layer class library is PolyApplet63. This class library has two groups of commands, with one group dealing with binary neural net and the other group dealing with multi-valued neural net. PolyNet63 refers to a component of the class library, PolyApplet63, which deals with the multi-valued commands.Part I � Neural Layer:
Chapter 3 introduces the PolyApplet63, the neural network layer class library. This class is further divided into two algorithms:
Chapter 4 attempts to build software like a simple version of the Attrasoft ABM 2.7, using PolyApplet63 (binary part).
- Abm63 (Binary Boltzmann Machine) and
- PolyNet63 (Multi-valued Boltzmann Machine).
Chapter 5 attempts to build software like a simple version of the Attrasoft PolyNet 4.0, using PolyApplet63 (multi-valued part).
Chapter 6 attempts to build software like the Attrasoft PolyNet 4.0, using PolyApplet63, i.e. add more functions to chapter 5.
Chapter 7 will use the Array commands for training and recognition. Array commands provide the neural net with data through array parameters, while File commands provide the neural net with data through files.
Part II � Presentation Layer:
- Array commands are used in the Attrasoft ImageFinder; and
- File commands are used in the Predictor and DecisionMaker.
Chapter 8 introduces the class library Abm2. It also attempts to build software like the Attrasoft Predictor 2.6, using PolyApplet63 (binary algorithm) and abm2. This chapter is focused on how to translate the Predictor input data into PolyApplet63 (binary algorithm) input data and how to translate the PolyApplet63 (binary algorithm) output data to Predictor output data.
Chapter 9 attempts to build prediction software using PolyApplet63 (multi-valued algorithm) and Abm2. This chapter is focused on how to translate the Predictor input data into PolyApplet63 (multi-valued algorithm) input data and how to translate the PolyApplet63 (multi-valued algorithm) output data to Predictor output data. The difference between chapter 8 and 9 is that two different algorithms are used at the neural net layer.
Chapter 10 attempts to build software like the Attrasoft DecisionMaker 2.5, using PolyApplet63 (binary) and Abm2. This chapter is focused on how to translate the DecisionMaker input data into PolyApplet63 (binary) input data and how to translate the PolyApplet63 (binary) output data to DecisionMaker output data.
Chapter 11 attempts to build function-inference software, using PolyApplet63 (multi-valued) and Abm2. This chapter is focused on how to translate the DecisionMaker input data into PolyApplet63 (multi-valued) input data and how to translate the PolyApplet63 (multi-valued) output data to DecisionMaker output data. The difference between chapter 10 and 11 is that two different algorithms are used at the neural net layer.
Part III � Application Layer:
Chapter 12 introduces the class library �Predictor63�. It also attempts to build software like the Attrasoft Predictor 2.6, using Predictor63.
Chapter 13 introduces the class library �PredictorPoly63�. It also attempts to build prediction software similar to the Attrasoft Predictor 2.6, with binary neural net being replaced by multi-valued neural net. The difference between chapter 12 and 13 is that two different algorithms are used at the neural net layer.
Chapter 14 introduces the class library �DecisionMaker63�. It also attempts to build software like the Attrasoft DecisionMaker 2.5, using DecisionMaker63.
Chapter 15 introduces the class library �DecisionMaker63�. It also attempts to build function-inference software similar to the Attrasoft DecisionMaker 2.5, with binary neural net being replaced by multi-valued neural net. The difference between chapter 14 and 15 is that two different algorithms are used at the neural net layer.
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