Through standard mathematical methods of statistics, we can obtain a large number of local structural spaces that can be expressed by functions. The neural network is usually optimized through a learning method based on mathematical statistics, so it is also a practical application of mathematical statistics. The modern neural network is a non-linear statistical data modeling tool. It is an adaptive system, or we say it has a learning function. In most cases, the artificial neural network can change the internal structure on the basis of external information. The neural network is calculated by connecting a large number of artificial neurons. Question: Take the Mind+ stage display method in the rotary dial telephone project as a reference, try producing the "Ali Baba and the Forty Thieves" animation project.Īrtificial Neural Network (ANN), referred to as Neural Network (NN), in the field of machine learning and cognitive science, is a mathematical model or calculation model that imitates the structures and functions of biological neural networks (animal's central nervous system, especially the brain), which is used to estimate or approximate the function. Question 2: Two neuron modules can "memorize" two password features at the same time, so can multiple neuron modules recognize more complex passwords? Furthermore, can they recognize Chinese characters and play Go with humans?Īnswer: The more neuron modules there are, the more signal features that can be learned, and that means more logic modules can handle more complex situations.įor reference: At the end of this lesson, you can assign homework to students as an extension of the course. Question 1: With the logic and knowledge learned earlier, if the logic OR module in the project is replaced by logic AND module, what function will be achieved, can you create application scenarios for them separately?Īnswer: The password box can be only opened when two passwords are both correctly rotated, and it is more difficult to open the password box. In a final analysis, the reason is that the characteristics of the two password signals are not the same, while a neuron module can only learn one feature at a time, so how can we let the project device learn two password signals?įor reference: In this part, you can summarize the curriculum project by raising questions to let students think and discuss so as to recall the content of this lesson and deepen the understanding of the project. If you want to qualify the second password signal through adjustment, you can only adjust the accuracy to the minimum, then the password box will be useless. When learning the second password signal, the first password signal will be overwritten and deleted Ģ. We can use the knob and Neurone module to make a password lock, but have you found that the Neurone module can only learn one password signal each time? If we let it learn another different password signal at the same time (that is, each of the password signals can open the box), then we will encounter the following troubles after learning the first password signal:ġ. Driving Question: The password box can store valuables.
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