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. |