Neural network fuzzy systems 5.4



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Neural network fuzzy systems - The Best App on Neural network & fuzzy systems, learn a topic in a minute

The app is a complete free handbook of Neural network, fuzzy systems which cover important topics, notes, materials, news & blogs on the course. Download the App as a reference material & digital book for Brain and Cognitive Sciences, AI, computer science, machine learning, knowledge engineering programs & degree courses. 

This useful App lists 149 topics with detailed notes, diagrams, equations, formulas & course material, the topics are listed in 10 chapters. The app is must have for all the engineering science students & professionals. 

The app provides quick revision and reference to the important topics like a detailed flash card notes, it makes it easy & useful for the student or a professional to cover the course syllabus quickly before an exams or interview for jobs. 

Track your learning, set reminders, edit the study material, add favorite topics, share the topics on social media. 

You can also blog about engineering technology, innovation, engineering startups,  college research work, institute updates, Informative links on course materials & education programs from your smartphone or tablet or at http://www.engineeringapps.net/. 

Use this useful engineering app as your tutorial, digital book, a reference guide for syllabus, course material, project work, sharing your views on the blog. 

Some of the topics Covered in the app are:

1) Register Allocation and Assignment
2) The Lazy-Code-Motion Algorithm
3) Matrix Multiply: An In-Depth Example
4) Rsa topic 1
5) Introduction to Neural Networks
6) History of neural networks
7) Network architectures
8) Artificial Intelligence of neural network
9) Knowledge Representation
10) Human Brain
11) Model of a neuron
12) Neural Network as a Directed Graph
13) The concept of time in neural networks
14) Components of neural Networks
15) Network Topologies
16) The bias neuron
17) Representing neurons
18) Order of activation
19) Introduction to learning process
20) Paradigms of learning
21) Training patterns and Teaching input
22) Using training samples
23) Learning curve and error measurement
24) Gradient optimization procedures
25) Exemplary problems allow for testing self-coded learning strategies
26) Hebbian learning rule
27) Genetic Algorithms
28) Expert systems
29) Fuzzy Systems for Knowledge Engineering
30) Neural Networks for Knowledge Engineering
31) Feed-forward Networks
32) The perceptron, backpropagation and its variants
33) A single layer perceptron
34) Linear Separability
35) A multilayer perceptron
36) Resilient Backpropagation
37) Initial configuration of a multilayer perceptron
38) The 8-3-8 encoding problem
39) Back propagation of error
40) Components and structure of an RBF network
41) Information processing of an RBF network
42) Combinations of equation system and gradient strategies
43) Centers and widths of RBF neurons
44) Growing RBF networks automatically adjust the neuron density
45) Comparing RBF networks and multilayer perceptrons
46) Recurrent perceptron-like networks
47) Elman networks
48) Training recurrent networks
49) Hopfield networks
50) Weight matrix
51) Auto association and traditional application
52) Heteroassociation and analogies to neural data storage
53) Continuous Hopfield networks
54) Quantization
55) Codebook vectors
56) Adaptive Resonance Theory
57) Kohonen Self-Organizing Topological Maps
58) Unsupervised Self-Organizing Feature Maps
59) Learning Vector Quantization Algorithms for Supervised Learning
60) Pattern Associations
61) The Hopfield Network
62) Limitations to using the Hopfield network

Each topic is complete with diagrams, equations and other forms of graphical representations for better learning and quick understanding. 

Neural network, fuzzy systems is part of Brain and Cognitive Sciences, AI, computer science, machine learning, electrical, electronics, knowledge engineering education courses and technology degree programs at various universities. 


About Neural network fuzzy systems

Neural network fuzzy systems is a free app for Android published in the Teaching & Training Tools list of apps, part of Education.

The company that develops Neural network fuzzy systems is Engineering Apps. The latest version released by its developer is 5.4.

To install Neural network fuzzy systems on your Android device, just click the green Continue To App button above to start the installation process. The app is listed on our website since 2018-01-10 and was downloaded 64 times. We have already checked if the download link is safe, however for your own protection we recommend that you scan the downloaded app with your antivirus. Your antivirus may detect the Neural network fuzzy systems as malware as malware if the download link to com.faadooengineers.free_neuralnetworkandfuzzysystems is broken.

How to install Neural network fuzzy systems on your Android device:

  • Click on the Continue To App button on our website. This will redirect you to Google Play.
  • Once the Neural network fuzzy systems is shown in the Google Play listing of your Android device, you can start its download and installation. Tap on the Install button located below the search bar and to the right of the app icon.
  • A pop-up window with the permissions required by Neural network fuzzy systems will be shown. Click on Accept to continue the process.
  • Neural network fuzzy systems will be downloaded onto your device, displaying a progress. Once the download completes, the installation will start and you'll get a notification after the installation is finished.



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Downloads: 64
Updated At: 2024-04-22
Publisher: Engineering Apps
Operating System: Android
License Type: Free