Artificial intelligence is the kind of intelligence that scientist has developed in computers. One of the ways of achieving AI is by using neural networks.
These neural networks are very much inspiret of the way they imagine our own brain works. Though we think we have quite a good idea on which processes goes on inside our brains,
nobody really knows why we are able to think the thoughts we do, and solve these abstract problems we are daily presented to.
Some people think the answer lies with the compleksity of our brain, so the scientists are far from actually creating intelligence at hight with human's,
because the human is so incredible complicated.
The Axon is used by the neuron to send out electrical signals to other neurons. The axon can be anything from a few millimetres to
metres in length. The Axon uses the sodium/potassium pump to generate these electrical signals. Below is a flash showing the transportation of signals in an axon.
A process or set of rules that are used for calculation or problem solving. In computer-science algorithms are frequently used to make a step-by-step solving of
difficult problems. The algorithm could for example guide one through a simple equation by telling one which numbers to divide or multipli with, and when to do what.
Sending data back through the system, checking if the output matches the wanted.
Actually back-probagation learning is a very logical way of learning, sometimes humans also have the need to look back to see if where we are, is actually the place we were suposed to be.
More information at:
http://www.bham.ae.uk/EAA/eaa96/abstracts/244.htm
Here back-probagation was used to investigate some very cool stuff, the problem was very abstract, so it was very relevant to use back-probagation
The neuron uses the dendrite to recieve electrical signals from other neurons.
The dendrite is only a small surface that is able to percept when the small bags of neurohormone is send there,
In the cerebral cortex, billions of neurons interact with each other to make the mind work. At certain stages the neurons form a firing pattern.
When a pattern has been learnt, the brain can recall certain firing patterns that matches the given input eg. speech, looks or a smell.
The linear combiner is the core of an artificial neuron. It is used to sum up all the synaptic input signals and
weights. The ways of the calculation will be explained to you, under the "sum-function" section.
In order to make a network able to solve more complex problems, one can be forced
to expand the network with several layers. Only the layers where computing processes takes place is counted in.
Ofcourse "multi" only means that there are several of them.
A hormone produced by nervecells and secreted into the circulation. The nurohormones is also the link between the different neurons in the brain.
When the Axon generates an electrical signal, it stimulates small bags of neurohormone to be sent over the gap between the neurons (the synapse)
These bags will carry the signal generated by the Axon to the recieving neuron.
This is a function that has too many factors to be computed using linear mathematics. This is the reason why we as humans concider ourselves so extraordinary, the ability to solve non-linear problems.
A non-linear problem is a problem that is so abstract that it can not be solved by a computer, for example emotional problems, there are simply too many factors for a computer to process.
We still seek to make artificial neural networks able to solve these problems, but in order to do that, we must first know how it is we do it ourselves.
A scientist who works with the processes inside the brain, and the rest of the nervous system.
Everything we know today about our own brain and it's functions, we know because of the research made by neurologists.
The basic building block in the brain and in a artificial neural network. The neuron consists of several dendrites that recieves information from other neurons. These
signals are led to the core, where it determins whether or not to send out a signal through the axon.
Object-oriented programming is a way of making objects containing their own code, variables and routines. In object-oriented programming the programmer doesn't
have to know about the internals of the object, but only an object interface.
perception is the process in which sensory stimulation is made into useful experience. Humans use perception as well, When we recieves data from our eyes, in form of flashing light, we can translate it into motion and all the things we see.
A perceptron is simply a systen that performs this action.
The term parallel is used in computer science when more than one piece of information is transfered simultaneously. Usually this is much more efficient than working
serial.
Recurrent neural networks is a network having one or more neurons that feeds data back into the network, so that they can alter their own input. This is ofcourse used when there is somthing wrong with the total output of the system
This is a function that is curved like the uncial "sigma". "Sigma is a letter in the ancient Greek alphabet. The function is smooth around 0 to 1 on the y-axis, when the x-value is close to 0.
A single layer perceptron actually consists of two layers of neurons, the input layer and the computational layer. The reason why to call it a single layered
network is that it is only in the last layer that computation is performed.
Between the neurons transmitters and recievers, there is a small gap. In order to pass this gap, the electrical signals causes small bags, containing a neurohormone, to be releasesd and send to the recieving neuron.
The synaptical strength depends on how many signals is send to one neuron. The signal may be send from many different transmitting neurons.
Synaptic strengths refers to the influence a synapse has on the neuron, it can either inhibit (excite) the neuron or exhibit (de-excite) the neuron.
The outcome is determined by the synaptical strength.
If sufficient neurons transmits a signal to one neuron, the synaptical strength will be high enough to excite the neuron, and it will send the signal on to the next neuron in the pattern.
The level of synaptical strength needed to excite the neuron is determined by which part it takes in the paticular firing pattern.
These two materials have a great importance in the neurological processes, using a dimorph cell membrane they are responsible for producing the electrical signals between the neurons.
Serial processing means that only one piece of data is processed at any one time. The one piece of information has to be processed before a new piece of information
can be processed. Nice word "processed"...
