**Wikipedia** says An Artificial Neuron or **The Mcculloch Pitts** Neuron is a mathematical function conceived as a model of biological neurons, a neural network.

**And now we are going to see What is Mcculloch Pitts Neuron and we are going to learn the Mathematics behind this neuron in the simplest way. **

**So, Let’s Get Started.**

**First of all, What is Biological Neuron?**

**A biological neuron consists Fours Parts Mainly,**

**Dendrite**– Receives signals from other neurons.**Synapse**– Point of connection to other neurons.**Soma**– It’s the CPU, it processes the information.**Axon**– Transmits the output of the neuron.

**Mccullouch Pitts Neuron**

As you can see **{X _{1, }X_{2, }X_{3, }…, X_{n}} ∈ {0,1}** are the

**Inputs**and

**Y ∈ {0,1}**is the

**Output**. And

**f**and

**g**are the

**Functions**.

f is the **Activation Function** and g is the **Pre-Activation Function**.

There are two types of inputs, One is **Excitatory** Input, which is dependent and another is **Inhibitory** Input, which is independent input.

Here **{X _{1, }X_{2, }X_{3, }…, X_{n}} ∈ {0,1} **are the Excitatory Inputs.

### Now, let’s see the Math behind this neuron.

# The output will be 1 if **g(x)** is **Greater than equal to ( ≥ )** the **threshold parameter** and the output will be 0 if **g(x)** is **less than ( < )** the **threshold parameter**.

**g(x)**

**Greater than equal to ( ≥ )**

**threshold parameter**

**g(x)**

**less than ( < )**

**threshold parameter**

## I hope its clear now.

**Notes: – **

**A single Mcculloch Pitts neuron can be used to represent Boolean functions ( AND, OR, NOR etc. ) which are linearly separable.**

**Linear Separability: There exists a line ( plane ) such that all inputs which produce a 1 lie on one side of the line ( plane ) and all inputs which produce a 0 lie on another side of the line ( plane ).**

Source: NPTEL’s Deep Learning Course

## Subscribe To Our Newsletter

Join our mailing list to receive the latest news and updates from our team.

## You have Successfully Subscribed!