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8/14/2019 Neural Computer Unlimited Memory
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NEURAL COMPUTER AND UNLIMITED MEMORY
IDEA PROPOSED BY
SREEKANTH PM
KERALA
KASARGOD (dt)
PH:+919747629216
HTTP://crazydiode.blogspot.com
NOTE: THIS WILL NOT CONTAIN A DETAIL REPORT ON
UNLIMITED MEMORY AND NEURAL COMPUTER.. IT IS UNDER
RESERCH THOSE WHO INTERESTED TO PARTICIPATE THE
RESERCH PROGRAMME CALL US +919747629216
OR MAIL US [email protected]
http://crazydiode.blogspot.com/mailto:[email protected]://crazydiode.blogspot.com/mailto:[email protected]8/14/2019 Neural Computer Unlimited Memory
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Mail ure resume here only talented person can get chance
NEURAL COMPUTER AND UNLIMITED MEMORY
INTRODUCTION
In this 21 st century, it is an era of new inventions and
discoveries. And in this era main experiment conducted on
neural network, IT and robotic technology. Both IT and
robotic technology is widely used in different areas and in
neural networks more invention are going. And in these days
we develop so many super computers as like param1,2 etc..this super computer invented for storing a large volume of
data and for getting a high processing speed, but it have
limitation that we seen in the experiment of LARGE HADRON
COLLIDE ,it is an experiment conducting in Europe and this
experiment is also known as the largest and dangerous
experiment conducted in this century. This experiment is
used for studying the condition of earth and universe before
big bang. The out coming result is important we cannot
avoid each information and this will happen in fraction of
seconds because these type experiment conducting on light
travelling speed so there should be highly efficient
computer for saving that data and in hadron collider if the
out coming results are stored in compact disc and it make it
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aligned it should have a length of 20 km in a day. Here we
need a high memory having high processing speed. For this
experiment here they used nodes of super computer and
also we know that secondary memory having less execution
than a processor. There we can propose a idea a unlimitedmemory, high processing speed as compared as our
imagination. That is my topic neural computer, innovative
thoughts and dreams an unlimited memory.
NEURAL COMPUTER
ABSTRACT
It is completely a new idea, our topic is to
make our selves as a computer and if there is resources
we can make unlimited storage memory through biological
and electronic concepts. This concept is work with the
basic principle of neural networks. In neural networks it
can not produce miracles, but sensibly they can produce
some amazing results.
Here we trying to make an artificial neural
network, An Artificial Neural Network (ANN) is an
information processing paradigm that is inspired by the
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way biological nervous systems, such as the brain, process
information. The key element of this paradigm is the novel
structure of the information processing system. It is
composed of a large number of highly interconnected
processing elements (neurones) working in unison to solvespecific problems. ANNs, like people, learn by example. An
ANN is configured for a specific application, such as
pattern recognition or data classification, through a
learning process. Learning in biological systems involves
adjustments to the synaptic connections that exist
between the neurones. This is true of ANNs as well.
In this topic our aim is to make storing a data to
brain or genomes that help us to remember through an
electronic device. we don't think that it is a one year
project. For this project we first consider how the neuron
activated while we learning something and which type of
pattern that it generated while we learning then we
converted our neuron through an electronic system
because we know that neuron produces a electric signal
corresponding to its input. For this we have to know how
human brain is learned some thing, Much is still unknown
about how the brain trains itself to process information,
so theories abound. In the human brain, a typical neuron
collects signals from others through a host of fine
structures called dendrites. The neuron sends out spikes
of electrical activity through a long, thin stand known as
an axon, which splits into thousands of branches. At the
end of each branch, a structure called a synapse converts
the activity from the axon into electrical effects thatinhibit or excite activity from the axon into electrical
effects that inhibit or excite activity in the connected
neurones. When a neuron receives excitatory input that is
sufficiently large compared with its inhibitory input, it
sends a spike of electrical activity down its axon. Learning
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occurs by changing the effectiveness of the synapses so
that the influence of one neuron on another changes.
next step is human neuron to artificial neurons for this
some scientists make a model programming it follows as
like this
engineering approach to this project
As above said we first learned how the neuron works and
what type of pulses that produce while we learning. We make a
electronic system that convert messages that are to be learned is
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converted to a form that it can stimulate the neuron and brain.
And we consider each rule in electronics in this field, for
describing these we need the help of FIRING RULE.The firing rule
is an important concept in neural networks and accounts for their
high flexibility. A firing rule determines how one calculateswhether a neuron should fire for any input pattern. It relates to all
the input patterns, not only the ones on which the node was
trained.
COURSE OF THOUGHT
This is a new concept, now it is just proposed this
idea and further researches are going very rapidly and the
research results were kept secretly because it have some
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ethical problems these will discuss latterly. Actually it a
idea come out for making a unlimited memory and it
should have high processing speed and we can avoid the
use of cache memory.
And for this concept the basics of this concept is neural
network.
In these days there is a innovative invention on artificial
neural networks. In this idea it mainly used biological
neuron accompanying with some basic principle used in
the artificial neural networks.
Concept behind this idea
Concept behind this idea is that choosing an
element for making a memory so here chose an element
that is neuron. The specialty for choosing neuron as an
element is that
1. Adaptive learning
Adaptive learning is the property of neural
network that is a neural net work can perform a work withconsidering its input. For a computer network there
should be programmed interface or its corresponding
software for identifying this or by manually we should
point that particular that input to a software in neuron
that is not needed that property is known as adaptive
learning.
2. Self organization
Self organization means a neural network can its own
organization or representation for given information.
3. Real time operation
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It is a special property of a neuron that it can performed a
multitasking job and in this modern world we performed
with the help of PLC and SCADA
4. FAULT TOLERANCEFault tolerance means a neural network have high
capability to avoid error or fault.
In modern devices such like processors these are the
main challenges. They improve to get these but for a
neuron it is a common property. Because of these
properties it can considered as an element to making an
un limited memory. In this memory system we used here
biological neuron as processors and data buses, we know
the processing speed of neuron for knowing processing
speed of neuron just analyze its reflex action and we can
see even light its travelling 3*10^8 m/s.
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BUILDING CONCEPTS OF A NEURAL COMPUTER
1.How a neural network performs an operation
i) FIRING RULE
The performance of neural network mainly
based on FIRING RULE.
A simple firing rule can be implemented by using Hamming distance
technique. The rule goes as follows:
Take a collection of training patterns for a node, some of
which cause it to fire (the 1-taught set of patterns) and
others which prevent it from doing so (the 0-taught set).
Then the patterns not in the collection cause the node to
fire if, on comparison , they have more input elements in
common with the 'nearest' pattern in the 1-taught set than
with the 'nearest' pattern in the 0-taught set. If there is a
tie, then the pattern remains in the undefined state.
For example, a 3-input neuron is taught to output 1 when the input
(X1,X2 and X3) is 111 or 101 and to output 0 when the input is 000
or 001. Then, before applying the firing rule, the truth table is;
X1: 0 0 0 0 1 1 1 1
X2: 0 0 1 1 0 0 1 1
X3: 0 1 0 1 0 1 0 1
OUT: 0 0 0/1 0/1 0/1 1 0/1 1
As an example of the way the firing rule is applied, take the pattern
010. It differs from 000 in 1 element, from 001 in 2 elements, from
101 in 3 elements and from 111 in 2 elements. Therefore, the
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'nearest' pattern is 000 which belongs in the 0-taught set. Thus the
firing rule requires that the neuron should not fire when the input is
001. On the other hand, 011 is equally distant from two taught
patterns that have different outputs and thus the output stays
undefined (0/1).
By applying the firing in every column the following truth table is
obtained;
X1: 0 0 0 0 1 1 1 1
X2: 0 0 1 1 0 0 1 1
X3: 0 1 0 1 0 1 0 1
OUT: 0 0 0 0/1 0/1 1 1 1
The difference between the two truth tables is called the
generalization of the neuron. Therefore the firing rule gives the
neuron a sense of similarity and enables it to respond 'sensibly' topatterns not seen during training.
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ii) DATA TRANSMISSION IN A BIOLOGICAL NEURON
A neuron is simply a transducer which converts physical energy to
electrical signals and it has following procedures:
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2. THRESHOLD NEURON
When a neuron is not sending a signal, it is "at rest." When a neuron is at rest, the inside of theneuron is negative relative to the outside. Although the concentrations of the different ions at-
tempt to balance out on both sides of the membrane, they cannot because the cell membrane al-
lows only some ions to pass through channels (ion channels). At rest, potassium ions (K+) cancross through the membrane easily. Also at rest, chloride ions (Cl-)and sodium ions (Na+) have a
more difficult time crossing. The negatively charged protein molecules (A-) inside the neuron
cannot cross the membrane. In addition to these selective ion
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channels, there is a pump that uses energy to move three sodium ions out of the neuron for every
two potassium ions it puts in. Finally, when all these forces balance out, and the difference in the
voltage between the inside and outside of the neuron is measured, you have the resting poten-
tial. The resting membrane potential of a neuron is about -70 mV (mV=millivolt) - this means
that the inside of the neuron is 70 mV less than the outside. At rest, there are relatively more so-
dium ions outside the neuron and more potassium ions inside that neuron.
Action Potential
The resting potential tells about
what happens when a neuron is at rest. An action potential occurs when a neuron sends informa-
tion down an axon, away from the cell body. Neuroscientists use other words, such as a "spike"
or an "impulse" for the action potential. The action potential is an explosion of electrical activitythat is created by a depolarizing current. This means that some event (a stimulus) causes the
resting potential to move toward 0 mV. When the depolarization reaches about -55 mV a neuron
will fire an action potential. This is the threshold. If the neuron does not reach this criticalthreshold level, then no action potential will fire. Also, when the threshold level is reached, an
action potential of a fixed sized will always fire...for any given neuron, the size of the action po-
tential is always the same. There are no big or small action potentials in one nerve cell - all ac-
tion potentials are the same size. Therefore, the neuron either does not reach the threshold or afull action potential is fired - this is the "ALL OR NONE" principle.
Action potentials
are caused by an exchange of ions across the neuron membrane. A stimulus first causes sodium
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channels to open. Because there are many more sodium ions on the outside, and the inside of the
neuron is negative relative to the outside, sodium ions rush into the neuron. Remember, sodium
has a positive charge, so the neuron becomes more positive and becomes depolarized. It takeslonger for potassium channels to open. When they do open, potassium rushes out of the cell, re-
versing the depolarization. Also at about this time, sodium channels start to close. This causes the
action potential to go back toward -70 mV (a repolarization). The action potential actually goespast -70 mV (a hyperpolarization) because the potassium channels stay open a bit too long.
Gradually, the ion concentrations go back to resting levels and the cell returns to -70 mV.
i)LOGICAL STATUS OF A THRESHOLD NEURON
1 2 (0 1 {0 1){1 1}}1 1 1 y; ; , x = - y- ,-y , x
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ii)PERCEPTRON(THRESHOLD) ACTIVATION FUNCTIONS
iii)THRESHOLD BOOLEAN FUNCTIONS
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Iv)THRESHOLD BOOLEAN FUNCTIONS AND THRESHOLD NEURONS
f x xn( ,..., )1 W w w wn= ( , ,..., )0 1
)...(),...( 1101 nnn xwxwwsignxxf +++=
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V)GEOMETRICAL INTERPRETATION OF THRESHOLD BOOLEAN FUNCTIONS
Tn
n20
23>
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ESSENCE OF THIS IDEA
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The objective and aim of this topic is that making a un limited memory by
using a neuron as a element. Neuron is not only an element by technically
it is a data bus. And for an un limited memory we need a storing or
memory for this we use our brain itself means human brain itself. Because
human brain have two parts
1 . short term memory
2. long term memory
In short term memory it act as like as a ram it can success only when we
are in conscious state and longterm memory is act like as a ROM in
computer memory. The entire data is stored in our long term memory that
is the cap[acity of oyr long term memory is unpredictable before the deep
study scientists thought that make long term memory as a memory
element.
And by using this long term memory as according to this idea all data
sends to brain to its long term memory without reading a lesson , without
seeing any visuals and without hearing any audio signals we can send a
data directly to brain. And this can be possible by stimulating neuron by
externally.
Stimulation of neuron can done externally by using a electric field.
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How we can stimulate a neuron externally
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External stimulation done in a bird
This is the set up done for the external stimulation of a bird is Zebra finc
and by stimulating its neuron they produce its sound and it decoded
directly from its brain by brain mapping technique.
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Transmission of data to the brain
A data can transfer to the brain with external stimulation and making a
signal corresponding to the data that have to store in the brain. For
making this we have to study each patern of the brain wave patern for
reading, visuals and this can taken by scanning such as MRI eeG ETC..
And studying each paterns we can produce externally that type of a
signal and by using a transmitter a computer interface we can send this
data directly to the brain.
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APPLICATION
1. By using this we can make unlimited memory
2. it can be used in hadron collider systems
3. if this is a success we can cure the disease parkinsons and paralysys
4. And another thing is that we can forget blindness, dumph and dump
etc..