Definitions of the vocabulary associated with Threshold logic units.

Term | Explanation |
---|---|

Action potential | The action potential is the potential difference across the cell membrane that is required to initiate a travelling pulse across the membrane. It is also the name of the pulse itself, and denotes any intra- or inter-cell signal. |

Activation function | Also known as the squashing function, it is a function used to transform the activation potential (or output of the summation unit) of a TLU into a bounded output signal. |

Afferent | Incoming. |

Artificial neuron | Computational model of a biological neuron, attempting to leverage useful neurobiological characteristics in human technology. |

Axon | Part of neuron which conducts action potentials to other neurons, site of output. |

Axonal hillock | Junction of axon and cell body. |

Binary classifier | A system which has two alternative input classifications |

Biological neuron | A real neuron, a cell which functions as a signal processing device. |

Boolean | A value, expression or function limited to the use of binary values: i.e:. true, false; high, low; 1, 0; +1, -1 and so on. |

Dendrite | A process connecting the afferent synapses and the soma. |

Dendritic tree | The branched structure connecting the afferent synapses with the soma. |

Efferent | Outgoing. |

Higher order polynomial | A Polynomial expression that is not linear. Typically used to describe expressions that contain terms involving a variable raised to a power. |

Heaviside function | A threshold, or step function. |

Hyperplane | An n dimensional equivalent of a straight decision line. |

Hypersurface | An n dimensional equivalent of a decision line (straight or otherwise). |

Input activation | Summation of the weighted input values |

Input line | An geometric description of an input value |

Input vector | The algebraic description of the input value in terms of its component values, or space co-ordinates |

Linear polynomial | A polynomial expression where each of the terms is either a constant, or a variable multiplied by a constant. |

Linearly separable | A pattern or set of data which can be divided geometrically by a straight line, plane or hyperplane. |

Network output | The output from the final node in the network. |

Neural network | A collection of simple processing units or nodes, loosely based on the biological neuron. |

Nonlinearly separable | A pattern or set of data which cannot be divided geometrically by a straight line. |

Output line | A geometric description of an output value. |

Output vector | The algebraic description of the output value in terms of its component values, or space co-ordinates. |

Polynomial | Algebraic expression presented in a simplified normal form, typically with addition on the outside, and progressively less 'linear' operators on the inside. |

Propositional logic | Classical logic without quantifiers. |

Signal | The transmission of a value from one location to another, or the value so transmitted. |

Sigmoidal function | An s-shaped, or semilinear function. e.g: 1/(1+exp(-av)). |

Soma | The cell body of the neuron containing the nucleus. |

State space | The conceptual space in which all the variables defining the state of a system form mutually orthogonal axes in an arbitrarily dimensioned space. |

Summation function | A function returning the sum of its arguments. |

Summation unit | The logical part of the TLU that contains the summation function. |

Synapse | Site of contact and chemical signal transmission between neurons. |

Synapse firing | For a chemical synapse, the release of a neurotransmitter substance from the pre-synaptic body upon the receipt of a signal pulse. Also the consequent emission of a new pulse from the post-synaptic body along the dendrite to the soma. |

Threshold axis | The axis marking the threshold value in the TLUs state space representation. |

Threshold hyperplane | The n-dimensional plane defined by a constant threshold value in the state space representation. |

Threshold logic unit | A simple example of an artificial neuron introduced by McCulloch and Pitts in the 1940s. |

Threshold unit | The logical part of the TLU that contains the threshold function. |

Threshold value | The input activation value at which the output of the threshold function changes. |

Vector | n-tuple viewed geometrically. Used to describe inputs, weights and outputs. |

Weight function | A function returning some multiple of its argument, where that multiple is equal to the weight value that corresponds to the argument. |

Weight value | The value that an input is multiplied by in the weight function. |