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\___: :___/\___: \/ \___/ \___/ ____ \___:
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__/ r e l e a s e \/_/ \_____\/_ / \ / \__ ___\/__(_ \___
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| Neural Networks made easy with Matlab |
| (c) Coursovie Training Inc. |
| |
| Publisher ....: Udemy |
| Level ........: all level |
| Runtime ......: 2 hours |
| Language .....: English |
| Release Type .: Retail |
| Release Format: ISO |
| Store Date ...: 2015.03.02 |
| Release Date .: 2016.01.28 |
| ISO Size .....: 314,368,000 |
| ISO Checksum .: 477CD2AF |
| Disk Count ...: 7 * 50MB |
| Disk Name ....: comprised_unnmewm |
| |
| Link/URL .....: http://v.gd/TU73k5 |
| |
| |
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: . _________________ __ ,,. __ ___\%%%%/________ ;;: : \ _____ :
__/ \/_/ \_____\/_ / \%%/ \__ ___\/__(_ \/__
_\ \ n o t e s /\ \/ \/ \ )/ _/
\ _\__________________\ / :
_\ \ |_
\/ _|/
| \_.
| Introduction : |
| |
| MATLAB (matrix laboratory) is a multi-paradigm numerical computing |
| environment and fourth-generation programming language developed by |
| MathWorks. Although MATLAB is intended primarily for numerical computing, |
| but by optional toolboxes, using the MuPAD symbolic engine, has access to |
| symbolic computing capabilities too. One of these toolboxes is Neural |
| Network toolbox. This toolbox is free, open source software for simulating|
| models of brain and central nervous system, based on MATLAB computational |
| platform. In these courses you will learn the general principles of Neural|
| Network Toolbox designed in Matlab and you will be able to use this |
| Toolbox efficiently as well. |
| |
| The list of contents is: |
| |
| Introduction û in this chapter the Neural Network Toolbox is Defined and |
| introduced. An overview of neural network application is provided and the |
| neural network training process for pattern recognition, function fitting |
| and clustering data in demonstrated. |
| |
| Neuron models û A description of the neuron model is provided, including |
| simple neurons, transfer functions, and vector inputs and single and |
| multiple layers neurons are explained. The format of input data structures|
| is very effective in the simulation results of both static and dynamic |
| networks. So this effect is discussed in this chapter too. And finally the|
| incremental and batch training rule is explained. |
| |
| Perceptron networks û In this chapter the perceptron architecture is |
| shown and it is explained how to create a perceptron in Neural network |
| toolbox. The perceptron learning rule and its training algorithm is |
| discussed and finally the network/Data manager GUI is explained. |
| |
| Linear filters û in this chapter linear networks and linear system design|
| function is discussed. The tapped delay lines and linear filters are |
| discussed and at the end of the chapter LMS algorithm and linear |
| classification algorithm used for linear filters are explained. |
| |
| Backpropagation networks û The architecture, simulation, and several |
| high-performance backpropagation training algorithms of backpropagation |
| networks are discussed in this chapter. |
| |
| Conclusion û in this chapter the memory and speed of different |
| backpropagation training algorithms are illustrated. And at the end of the|
| chapter all these algorithms are compared to help you select the best |
| training algorithm for your problem in hand. |
| |
| Matlab Software Installation: You are required to install the Matlab |
| Software on your machine, so you can start executing the codes, and |
| examples we work during the course. |
| |
| What am I going to get from this course? |
| |
| At the end of this course you are a confident Matlab Programmer using the |
| Neural Network Toolbox in a proper manner according to the specific |
| problem that you want to solve. |
| |
| In this course you will learn some general and important network structures|
| used in Neural Network Toolbox. |
| |
| By the end of the course, you are familiar with different kinds of training|
| of a neural networks and the use of each algorithm. You will learn how to |
| modify your coding in Matlab to have the toolbox train your network in |
| your desired manner. |
| |
| At the end, different types of training algorithm are compared using some |
| benchmarks to show the ability of each algorithm and at the same time to |
| provide good examples that the student can use for more practice. |
| |
| At last you are fully able to solve any engineering and technical Neural |
| Network project offered at University or College |
| |
| |
| |
| |
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:___/\______) ::::; :: /________________\%%%%%%/_____________\ ..::..:: .: ;.
;; _________________ __ .::; __ ___\%%%%/________ \ _____ ;
__/ a b o u t \/_/ \_____\/_ / \%%/ \__ ___\/__(_ \/__
_\ \ t h e g r o u p /\ \/ \/ \ )/ _/
\ _\__________________\ / :
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\/ No news is good news! _|/
| \_.
| |
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| |
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:___/\______) ,.::;; ;. /________________\%%%%%%/_____________\ ...,:::; ;.;:
:: _________________ __ ::; __ ___\%%%%/________ ...:: \ _____ ;
__/ \/_/ \_____\/_ / \%%/ \__ ___\/__(_ \/__
_\ \ g r e e t s /\ \/ \/ \ )/ _/
\ _\__________________\ / :
_\ \ |_
\/ Some hardworking groups, and maybe you? _|/
| \_.
| |
| |
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