steps on nn ...

Documents/NN/Documents.md

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+# Concepts of a Neural Network (NN)
+
+simulation of human nervous system in its ability to learn and adpt.
+
+## Units
+
+1. Inputs
+2. Weights
+3. Transfer Function + net output
+4. Activation Function
+5. Outputs
+
+### Flow
+
+1. Update and Provide our Inputs;
+2. Transfer Function;
+3. Net OutPut (Inputs and Weights);
+4. Actiation Function;
+5. Calculate Output;
+
+### Learnign
+
+it is a process to Change Weights of inputs based on results ...
+this happens to algorithm improve itself optimization ...
+
+### Net
+
+in this process Inputs and their Weights collecting together.
+
+### Activation Function
+
+Recieved Net Inputs (Weighted Inputs) and then Calculate output based on them.
+
+## Multi Layer NN
+
+1. Input Layer;
+2. Hidden Layer;
+3. Output Layer;
+
+Hidden Layers recieved Data from all other layers at the end, then Populate as a Neuron.
+
+### Input Data Normalization
+
+a Process where all the input data normalized.
+reduce data to an accepted ranges.
+i.e. [0,1] or [-1, 1].
+
+this peocess so important for us for making data more acceptable.
+
+this can done by some standard form:
+
+y = x - (x(min) * (d2 -d1)) / x(max - x(min)) + d1
+
+x => value to normalized;
+x(min)/x(max) => x Value range max and min;
+d1,d2 => ranges to upper and lower normalization;
+
+### Activation Functions
+
+a function which calculate the output of a neuron.
+it recieved a Net Input (Weighted functions);
+
+1. Unit Step / Hard Threshold Functions;
+2. Sigmoid Function;
+3. Hyperbolic Tangent Function;
+
+## Unti Step
+
+a Graph by y axix Output and x axix Net Input and values in y between 0, 1 and x is 0 to TETA or threshold.