=Paper=
{{Paper
|id=Vol-2870/paper127
|storemode=property
|title=Simulation of Logic Elements in Reverse Mode for Building Neural Networks
|pdfUrl=https://ceur-ws.org/Vol-2870/paper127.pdf
|volume=Vol-2870
|authors=Serhii Tsyrulnyk,Volodymyr Tromsyuk,Valentyna Vernygora,Yaroslav Borodai
|dblpUrl=https://dblp.org/rec/conf/colins/TsyrulnykTVB21
}}
==Simulation of Logic Elements in Reverse Mode for Building Neural Networks==
Simulation of Logic Elements in Reverse Mode for Building
Neural Networks
Serhii Tsyrulnyk, Volodymyr Tromsyuk, Valentyna Vernygora and Yaroslav Borodai
Vinnytsia Technical College, Khmelnytske highway, 91/2, Vinnytsia, 21000, Ukraine
Abstract
The hardware implementation of a feedback neural network, which is based on two ideas:
Stephen Grasberg’s adaptive resonance theory and Hopfield's auto-associative memory,
requires that all elements be connected by direct and feedback connections. This paper
presents a simulation of ordinary logic elements, but with reversible properties. The proposed
structure allows the signals to move both in the forward and the opposite directions. In
practice, this will mean that with the help of control signals, neuron signals can be directed
along the same lines of communication in different directions. In this way, all elements of the
system will be interconnected and the system will be able to remember and choose the best
way to solve the problem.
The authors propose modeling of ordinary logic elements using a special inclusion scheme
based on resistive dividers, which allows providing their reversible mode of operation. It is
also proposed to use the following logical elements to build neural networks such as the
Cosco architecture.
The work simulates the reversible operation of the following logical elements: 1) repeater
(buffer); 2) inverter; 3) the logical element NAND; 4) logical element NOR.
Keywords 1
Logic element, buffer, inverter, NAND, NOR, neural network
1. Introduction
The hardware implementation of neural networks is no less important than the development of
algorithms and software for the training and operation of artificial intelligence. To build any device or
network requires building materials, i.e. a set of similar and simple structural components. In
conventional digital technology, structural units are logical elements that can be used to implement
any function. In neural networks, such structural units are neurons. Conventional logic elements can
also be used to build connections between neurons and some parts of neurons. However, these logical
elements must work in reverse mode to ensure the reverse propagation of Verbos [1].
Logical elements with feedback should be used to build fully connected networks. A characteristic
feature of neural networks of this type is the presence of connections between all neurons [2, 3]. The
most well-known type of fully connected network is Hopfield networks (Fig. 1). In them, each neuron
has two-way connections with all other neurons in the network. In the general case, the Hopfield
network has a symmetrical ring structure, it is impossible to identify hidden neurons and a single
direction of signal propagation. The operation of a fully connected neural network and data exchange
is controlled by one main neuron [2].
The main problem that hinders the practical application of most neural networks is the complexity
and high complexity of the learning process. The use of reversible logic elements allows you to avoid
COLINS-2021: 5th International Conference on Computational Linguistics and Intelligent Systems, April 22–23, 2021, Kharkiv, Ukraine
EMAIL: sovm@ukr.net (S. Tsyrulnyk); 2013tvd@gmail.com (V. Tromsyuk); valentina.vernugora@vtc.vn.ua (V. Vernygora);
bortamugoo@gmail.com (Y. Borodai)
ORCID: 0000-0002-5703-9761 (S. Tsyrulnyk); 0000-0001-5022-8159 (V. Tromsyuk).
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
adjusting the feedback when learning the neural network. This idea is the basis of Jagger's proposed
recurrent neural network ESN (Echo State Network) [4-6], schematically depicted in Figure 2. During
its training, only the direct connections of the neurons of the hidden layer with the effectors are
modified. The forward and feedback connections between the neurons of the hidden layer do not
change. Some ESN models may also have constant feedback between effector outputs and hidden
layer neuron inputs.
Output
Input
Figure 1: Fully connected Hopfield network
In cases where you want to combine two-way communication lines, such as from a programmer or
debugger to a microcontroller or between two microcontrollers, you can also use reversible logic
elements as a prototype of a fully connected neural network to simplify the circuit [2-4].
Layer of
effectors
Hidden
Receptor layer
layer
Figure 2: Echo State Network
The connections of the hidden layer of the network are established when it is created and are
permanent random values. Since only direct connections with effector neurons are modified during
training, the responses of effector neurons of the ESN network reflect the linear compositions of the
dynamic responses of latent layer neurons [4-6].
To study the circuits of reversible logic elements requires information about the features of their
inputs and outputs in normal operation. Today there is a large variety of element base with Z state of
outputs, which allows you to easily use them in reverse mode. Elements with three states are widely
used in microprocessor technology to connect the pins of various devices of the microprocessor
system to a common bus. However, in some cases, it is interesting and even necessary to use the usual
element base in reverse mode. Reversible operation of logic elements allows signals to move along
the same line in both directions but at different times. In addition, the signal can be processed by the
same logic element, both in the forward and reverse directions. When using the reversible mode of
logical elements, it is possible to achieve reversible calculations in the neural network [8-10].
2. Inputs and outputs of logic elements
To understand the logic of reversible operation of logic elements, it is necessary to understand the
models of inputs and outputs of these elements [11-13].
At the first level of representation of the logical model and even the second level of representation
about the inputs of the chips, do not need to know anything at all. The input is considered as an
infinitely large resistance, which does not affect the connection of circuit elements. However, the
number of inputs connected to one output affects the signal propagation delay.
Even at the third level of representation of the electrical model in most cases, it is not necessary to
know about the internal structure of the chip and the circuitry of its inputs. When using a logic zero
input signal, a current not exceeding I1L (minimum allowable current) flows from this input, and when
a logic unit signal is applied, a current not exceeding I1H (maximum allowable current) flows into this
input. In addition, for the correct logic of the chip, it is enough that the voltage level of the input
signal of the logic zero was less than U1L, and the voltage level of the input signal of the logic unit
was greater than U1H.
A special case is a situation when any input is not connected to any of the outputs, or the common
wire, or the power bus (the so-called hanging input). Sometimes the capabilities of the chip are not
fully used, and some inputs do not send signals. However, the chip may not work or work erratically,
as its proper inclusion implies the presence of logic levels at all inputs. When such a chip is used in a
neural network, all outputs must always be used for signal processing.
The outputs of the chips are fundamentally different from the inputs in that taking into account
their features is necessary even at the first and second levels of representation.
There are three types of output stages, which differ significantly, both in their characteristics and
in application [11].
1. Standard output or output with two states (denoted by 2C, 2S or, less frequently, TTL, TTL);
2. Output with an open collector (denoted OK, OС);
3. Output with three states or (high-impedance, Z-state) with the possibility of disconnection
(denoted by 3С, 3S).
The standard output 2C has only two states: logical zero and logical one, and both of these states
are active, i.e. the output currents in both of these states (I0L and I0H) can reach appreciable values.
At the first and second levels of representation, such outputs can be considered to consist of two
switches that are closed alternately (Fig. 3), and the circuit of the upper switch corresponds to the
logic unit at the output and the circuit of the lower – logical zero.
Ucc
Ucc Ucc
Output 2С Output 3С
Output OK
EZ
Figure 3: Three types of outputs of logic elements
The output with the open collector OK also has two possible states, but only one of them (the state
of logical zero) is active, ie provides a large inflow current I0L. The second state is essentially
reduced to the fact that the output is completely disconnected from the inputs connected to it. This
state can be used as a logic unit, but for this purpose between the output OK and the supply voltage, it
is necessary to connect a load resistor R of the order of hundreds of kOhm (in our case 200 kOhm).
The output with three states of the 3C is very similar to the standard output, but to the two states is
added a third - passive, in which the output can be considered disconnected from such a scheme. At
the first and second levels of representation, such an output can be considered to consist of two
switches (Fig. 3), which can be closed alternately, giving a logical zero and a logical unit, but can also
open simultaneously. This third state is also called high-impedance or Z-state.
For example, if signals from two outputs need to be applied to the same input in turn (Fig. 4), then
outputs 2C are not suitable for this, but outputs OK and 3C are suitable. That is, logic elements with
such outputs can be used in reverse mode to build multidirectional neural networks.
Ucc
Ucc Ucc
Output 2C Output 3С
Output OK
Іsc EZ
Ucc Ucc
Output 2С Output OK Output 3С
EZ
Figure 4: Combining the outputs of logic elements
When combining two or more outputs 2C, one output may give a signal of a logical unit, and the
other – a signal of logical zero. It is easy to see that in this case, through the upper closed key of the
output, issuing one, and through the lower closed key of the output, issuing zero will go unacceptably
high short-circuit current Isc. This is an emergency in which the level of the received output logic
signal is not precisely defined, it can be perceived by the subsequent input as zero and as one.
Conflicting outputs can even fail, disrupting chips and circuits in general. Logic elements with such
outputs can be used in reverse mode, but only in special switching circuits that will prevent short
circuits.
However, in the case of combining the two outputs of the OK, such a conflict in principle cannot
happen. Even if the key of one output is closed and the other is opened, an emergency will not occur,
because there will be no unacceptably large current, and the combined output will have a logic zero
signal. And when combining two outputs of the Armed Forces, an emergency is possible (if both
outputs are simultaneously in the active state), but it can be easily prevented if you organize the
circuit so that only one of the combined outputs of the Armed Forces will always be in the active
state. [11-13].
Combining the outputs of logic elements in the bus organization of communication between digital
elements to form simple neural networks. Most often, the bus organization is used in microcontroller
devices; it simplifies the scheme, but is not yet a neural network. This approach allows generalized
modeling of neural networks on standard logic elements [2-4, 11].
By bidirectional, lines are understood such lines (wires), the signals of which can propagate in two
opposite directions. Unlike unidirectional lines that go from one output to one or more inputs,
multiple outputs and multiple inputs can be connected to a two-way line at the same time (Fig. 5).
Bidirectional lines can be organized only based on the outputs of the OK or AP [11-13]. Therefore,
almost all buffers have just such outputs. The construction of a neural network implies that all logical
elements are interconnected, both at the input and at output. It is the reversible inclusion of logical
elements that can provide the hardware of the neural network to provide logical calculations of
artificial intelligence [14-17].
In. Out In. Out. In. Out. In. Out.
Figure 5: Bidirectional line connecting logical elements
A bidirectional line must be multiplexed, and a multiplexed line can be both unidirectional and
two-way. In any case, it is joined by several outputs, only one of which at any given time is in the
active state. The remaining outputs are currently disabled (switched to passive state). Unlike a two-
way line, only one input can be connected to a buffer-based multiplexed line, but necessarily several
outputs from the OK or 3C [11].
3. Simulation of logic elements in reverse mode in Multisim environment 12
Reversibility in the operation of electronic devices allows equivalent transmission and/or signal
processing through these devices in the direction from input to output, and in the opposite direction
[14-21], i.e. the inputs and outputs of reversible devices are mutually inverted. The study of the
operation of logic elements in reverse mode is to build a switching circuit that allows the logic signal
to flow, both in the forward and reverse directions [14-15, 20-21]. To do this, you need to provide a
large input resistance at the input of the logic element: more than 50 kOhm and a load resistance of
the order of several 100 kOhm. The output resistance to avoid subsidence of the output signal level
must correspond to the ratio [20]:
𝑅𝑖𝑛 ≥ 2𝑅𝑜𝑢𝑡,
where Rin and Rout – input and output pair of reversible logic element.
To ensure minimal amplitude-frequency distortion of the output logic signals, the circuit of the
logic elements must be symmetrical, both in input and in output. At such inclusion, logical elements
will work equally both indirect inclusion and in return (Figure 6). When a signal source (IN) is
connected to terminal b, the load to terminal a of the logic element will operate in direct connection
(input on the left and output on the right). When a signal source (IN) is connected to pin a, the load on
pin b of the logic element will operate in reverse (input on the right and output on the left).
b
a
5R 2
1 5R
G1
b a
OUT
logical
IN element 10R
R R
Figure 6: Scheme of inclusion of a logical element
If you provide the connection of several inputs of the logic element, the symmetry will be broken,
which will lead to a slight distortion of the output signal. However, this will provide information
about the current state of the input signals, which will be shown later in the process of modeling
reversible logic elements.
3.1 . The Buffer simulation in Multisim environment 12
Figure 7 shows a diagram of the study of the buffer 4010VS1 in reverse mode. The circuit consists
of: a rectangular signal generator G1 with a frequency of 100 kHz and a voltage of 5V; resistors R1
and R3 to provide high input resistance; resistors R2 and R4 to provide output decoupling (matching
output resistances); load resistance R5 (signal receiver); switches SA1 and SA2, which act as
controllers, determining the input and output of the reversible logic element, in this case, the buffer.
Figure 7: Scheme of the study of the buffer direct inclusion
Figure 8 shows the timing diagrams of the buffer indirect inclusion, which show that such a logic
element repeats the input signal without significant distortion. The delay of the output signal for the
test buffer is 124 ns.
To study the buffer in inverse mode, you need to switch switches SA1, SA2 to the opposite value.
In this case, the signal is fed to the right (in the previous scheme it was the input) and removed to the
left (in the previous scheme it was the output).
Figure 8: The Oscillograms of the buffer in the direct-on mode
The results of the study of the buffer in the inverse mode are shown in Figure 9. The delay of the
output signal for the studied buffer is 124 ns.
Figure 9: The Oscillograms of the buffer in the reverse mode
From Figures 8 and 9 it is seen that the studied circuit of the inverter works the same, both in
direct connection and in reverse. It is determined that the output signal delay is 124 ns, and the buffer
is limited to a maximum frequency of 100 MHz.
3.2 . The Inverter simulation in Multisim environment 12
Figure 10 shows the study diagram of the inverter NC7SZU04. The circuit consists of: a generator
of rectangular signals G1 with a frequency of 100 kHz and a voltage of 5V; resistors R1 and R3 to
provide high input resistance (100 kOhm); resistors R2 and R4 to provide output decoupling (20
kOhm); load resistance R5 (200 kOhm); switches SA1 and SA2, which act as controllers, determining
the input and output of the reversing inverter; inverter NC7SZU04.
Figure 10: The scheme of the study of the inverter direct connection
Figure 11 shows the timing diagrams of the inverter in direct inclusion, which shows that such a
logic element inverts the input signal without significant distortion. The delay of the output signal for
the investigated inverter is equal to 5ns. Negative voltage output at the beginning of the pulses and
positive - at the end of the pulses is 0.3V.
Figure 11: The Oscillograms of the inverter in the direct-on mode
Figure 12 shows a study diagram of the inverter NC7SZU04 in reverse inclusion. In this case, the
input of the element to the right, where previously there was input, and the output to the left, where
previously there was an output. This ensures the reversibility of the investigated logical element.
Figure 12: The scheme of the study of the inverter in reverse inclusion
Figure 13 shows the timing diagrams of the inverter in reverse switching, which show that such a
logic element inverts the input signal with a delay of the output signal of 5.5ns and a negative voltage
output at the beginning of the pulses and positive at the end of the pulses 0.32V.
Figure 13: The Oscillograms of the inverter in reverse mode
The results of the study of the inverter in reverse mode show that such a logic element works the
same in both cases. Although due to the above switching scheme there are some insignificant
amplitude-frequency distortions of the output signal (0.3-0.32V), which can be easily eliminated
using amplitude limiters.
3.3 . The Logical element of NAND simulation in Multisim environment 12
Figure 14 shows a diagram of the study of the basic logic element NAND (NC7SZ00) in the mode
of direct inclusion. In this inclusion, the logic element NAND (Figure 15) works like a normal
inverter with a delay of the output signal of 5.8ns and voltage output of 0.32V.
Figure 14: The scheme of research of the logical element of NAND in direct inclusion
Figure 15: The Oscillograms of the logical element of NAND in the mode of direct inclusion
If one of the inputs of the logic element NAND is rigidly set to a value of logical zero, it will not
work in normal mode. It will work as a voltage repeater with a significant drop in the level of the
output logic signal.
Figure 16 shows a diagram of the study of the logic element NAND NC7SZ00 in direct connection
in the case when the inputs are connected to two input signals. The pulse duration of the first signal is
2 times less than the pulse duration of the second signal. That is, the frequency of the first signal is 2
times higher than the frequency of the second signal. This inclusion allows you to explore all possible
combinations at the input of the element NAND, both in direct inclusion and in reverse.
Figure 16: The Scheme of research of a logical element of NAND direct inclusion, at the connection
of two sources of logical signals
Figure 17 shows the timing diagrams of the logic element NAND in direct connection, which
shows that the delay of the output signal is 5.8ns, and the amplitude emission is 0.32V. In the pause,
the signal differs from the logic zero by 0.32V, now when on both inputs of a logical element logical
zero, subsidence of an output signal on 0,32V with a delay of 5.8ns is observed.
Figure 17: Oscillograms of operation of a logical element of NAND direct inclusion at the connection
of two sources of a signal with different frequency
Figure 18 shows the timing diagrams of the logic element NAND in the reverse inclusion (in the
diagram Figure 16, it is necessary to translate the switches SA1, SA2 in the opposite state). In the
pause, the signal differs from the logic zero by 0.32V, now when at both inputs of the logic element
logic zero, there is a sag of the output signal by 0.32V with a delay of 5.8ns. At the first input a
logical unit, and at the second input a logical zero. In this case, this is due to the transition of the logic
signal from the state of logical zero to the state of the logical unit and the violation of the symmetry of
the connection of the second input of the logical element NAND.
Figure 18: Oscillograms of operation of a logical element of NAND in reverse inclusion at the
connection of two sources of a signal with different frequency
The results of the study of the basic element NAND show that it can work as an inverter, or as a
classical element NAND when applying to its input arbitrary variables in time logic signals. However,
it is not able to work in normal mode, when one of the inputs will be rigidly set to logical zero. When
this is enabled, it, according to the logic of operation, must always output a logical unit, but works as
a buffer, but with a significant sag of the output voltage. The advantage of this switching scheme is
that when analyzing the output signal, namely the analysis of voltage emissions, you can tell exactly
what signals were on each of the inputs of the logic element at a particular time, i.e. this element can
store information about the input signals in the output logic signals. The circuit of the reversible logic
element NAND is limited to a maximum frequency of 200 MHz.
3.4 . The Logical element of NOR simulation in Multisim environment 12
Figure 19 shows a diagram of the study of the basic logic element NOR (NC7SZ02) in the mode
of direct inclusion. In this case, one input is a time-varying logic signal, and the other input is a hard-
set logic zero. In this inclusion, the logic element NOR (Figure 20) works like a normal inverter with
a delay of the output signal of 6ns and voltage output of 0.28V. If you apply to the second input of a
logic element NOR non-logic unit (VCC), then the logic of such an element should always give a
logical zero at the output, but it will work as a buffer with a significant sag of the output logic signal.
Thus such scheme works equally, both in the mode of direct and in the mode of return inclusion.
Figure 19: The scheme of the study of the logical element NOR direct inclusion
Figure 20: The Oscillograms of operation of a logical element NOR in the mode of direct inclusion
Figure 21 shows a diagram of the study of the logic element NOR (NC7SZ02) in the mode of
direct inclusion, in the case when both inputs are logic signals time variables. The frequency of the
first signal is 2 times higher than the frequency of the second signal, which allows us to investigate
the properties of this logic element for all possible combinations of logic signals at both inputs. Figure
22 shows the timing diagrams of the logic element NOR in direct connection when connected to both
inputs of the sources of logic signals with different frequencies. Such a logic element is characterized
by voltage emissions of 0.26V at times when both inputs have a logic unit and small short-term
(duration 6.5ns) voltage emissions when the input signals change to opposite values. Thus, by
analyzing the output signal for delays and voltage emissions, you can great reliability obtain
information about the input logic signals at a given time.
Figure 21: The scheme of the study of the logic element NOR direct connection when connecting
two signal sources
Figure 22: Oscillograms of the logic element NOR direct connection when connecting two signal
sources with different frequencies
To study the circuit of the logic element NOR (NC7SZ02) (Figure 21) in the reverse connection
you need to turn the switches SA1, SA2 in the opposite state. Figure 23 shows the timing diagrams of
the logic element OR in reverse when connected to both inputs of the sources of logic signals with
different frequencies. Voltage voltages of 0.26V with a delay of 6.5ns characterize such a logic
element at times when there is a logic unit at both inputs and small short-term voltage emissions when
the input signals change to opposite values.
Figure 23: Oscillograms of operation of a logic element NOR in reverse inclusion at the connection of
two sources of a signal with different frequency
The results of the study of the basic element NOR show that it can work as an inverter, or as a
classical element NOR when applying to its input arbitrary variables in time logic signals. However, it
is not able to work in normal mode, when one of the inputs will be rigidly installed logical unit. When
this is enabled, it, according to the logic of operation, should always output a logical zero, but works
as a buffer, but with a significant sag of the output voltage. The advantage of this switching scheme is
that when analyzing the output signal, namely the analysis of voltage emissions, you can tell exactly
what signals were on each of the inputs of the logic element at a particular time, i.e. this element can
store information about the input signals in the output as well as well as the element NAND.
The circuit of the reversible logic element NOR is limited to a maximum frequency of 180 MHz.
The power supply of logic elements operating in reverse mode can be carried out both in the usual
way, from DC power supplies (Figure 24, a), and one or more external pulse signal generators (Figure
24, b), by summing them, for example, adder and subsequent filtration filter R1C1 [20]. Such a load
will not affect the shape and amplitude of the signals of the generators. Note that the diode-resistive
circuit protection of the inputs and outputs of CMOS chips allows their operation in low-current
modes without the use of its power supply when applying signals to the input(s) of the chip.
4. Conclusions
Despite the indisputable achievements of the last 10 years in the development of the theory and
practical implementation of neural networks, they remain the subject of further intensive research.
The neural network proposed by D. Hopfield was compared either with spin-glass – a metastable
physical system, or with an associative memory-model of the nervous system of the brain. For a long
time, it was ignored, because neural networks were seen as a means of solving applied problems
through learning, in which the Hopfield neural network was inferior to the more flexible multilayer
networks of direct propagation.
G1 G2
VD1 VD2
R1
+E
14 14
С1 DD1 С1 DD1
7 7
a) b)
Figure 24: Options for connecting the power supply to the chips: a) a typical power on;
b) organization of power supply from generators
Building neural networks of this type require bricks that will consist of the entire structure. Such
elements can be even usual logical elements if to use special schemes of inclusion. In the real scheme,
the resistances of the n-p junctions of semiconductor transistors, and the switches control signals
using multiplexers or other logic switching elements must replace the resistors.
A study of the reversible operation of logic elements has shown that they can work equally in both
direct and reverse inclusion. In this case, the two-input elements can output information, in the output
logic signal, about the state of the inputs at a given time. To obtain reliable information about the state
of the inputs, you need to analyze the output signal for delays and sagging of the level of the output
logic levels based on the logic of the logic element.
For such elements there is no difference between input and output, the main thing is to ensure the
ratio of resistance between the signal source and the load.
The main task of this work was to show in principle the possibility of using ordinary logic
elements in reverse mode. Because of the simulation, it was proved that the logic elements could work
in reverse mode, using a special circuit of resistive dividers.
5. References
[1] Werbos, P.J.: Beyond Regression: New Tools for Prediction and Analysis in the Behavioral
Sciences; Ph.D. thesis. Harvard University: Cambridge, MA (1974)
[2] Kononyuk, A. Yu.: Neironni merezhi i henetychni alhorytmy. Kyiv: Korniychuk. 446 p. (in
Ukrainian) (2008)
[3] Kosko, B.: Competitive adaptive bi-directional associative memories. In: Proceedings of the
IEEE First International Conference on Neural Networks, eds. M. Caudill and C. Butler. San
Diego, V. 2, pp. 59 – 66 (1987)
[4] Riznyk, A.M.: Dynamichni rekurentni neironni merezhi. In: Mathematical Machines and
Systems, V. 2, pp. 3 – 26. (in Ukrainian) (2009)
[5] Jaeger, H.: Reservoir Riddles: Suggestion for Echo State Network Research. In: Proceedings
of International Joint Conference on Neural Networks. Canada, July 31 Aug. 4, pp. 1460 – 1462
(2005)
[6] Cernansky, M., Macula M.: Feed-forward Echo State Networks. In: Proceedings of International
Joint Conference on Neural Networks. Canada, July 31 Aug. 4, pp. 1479 – 1482 (2005)
[7] Merkle, R.C.: Towards Practical Reversible Logic. In: Workshop on Physics and Computation,
PhysComp. Texas: IEEE press (1992)
[8] Fredkin, E., Toffoli, T.: Conservative logic. In: International Journal of Theoretical Physics, V.
21, pp. 219 – 253 (1982)
[9] Nepeyvoda, N.N., Skopin, I.N.: Osnovyi programmirovaniya. Moscow-Izhevsk: RHD. 686 p. (in
Russian) (2004)
[10] Nepeyvoda, N.: Reversivnyie konstruktivnyie logiki. In: Logical Investigations, V. 15, pp. 150 –
168 (in Russian) (2009)
[11] Novikov, Yu.V.: Osnovyi tsifrovoy shemotehniki. Bazovyie elementyi i shemyi. Metodyi
proektirovaniya. Moscow: Mir. 379 p. (in Russian) (2001)
[12] Omatu, S.: Classification of mixed odors using a layered neural network. In: International
Journal of Computing, V. 16, pp. 41 – 48 (2017)
[13] Kravets, V.O., Sokol, E.I., Rysovany, O.M.: Kompiuterna skhemotekhnika. Kharkiv: NTU KhPI.
480 p. (in Ukrainian) (2007)
[14] Kravets, P.I., Shymkovych, V.M., Samotyy V.: Method and technology of synthesis of neural
network models of object control with their hardware implementation on FPGA. In: Proceedings
of the 2017 IEEE 9th International Conference on Intelligent Data Acquisition and Advanced
Computing Systems; Technology and Applications IDAACS, V. 2, pp. 947 – 951 (2017)
[15] Kruglov, V.V., Borisov, V.V.: Iskusstvennyie neyronnyie seti. Teoriya i praktika. Moscow:
Goryachaya liniya-Telekom. 382 p. (in Russian) (2002)
[16] Han, J., Li, Z., Zheng, W., Zhang, Y.: Hardware implementation of spiking neural networks on
FPGA. In: Tsinghua Science and Technology, V. 25, pp. 479 – 486 (2020)
[17] Skansi, S.: Introduction to Deep Learning. New York: Springer International Publishing. 189 p.
(2018)
[18] Shustov, M.A., Shustov, A.M.: Electronic Circuits for All. London: Elektor International Media
BV. 397 p. (2017)
[19] Tsyrulnyk, S.M., Roptanov, V.I., Zymoglyad, A.S.: Praktychni pidkhody do zastosuvannia
MIMS-Efekt. In: Optoelectronic information and energy technologies, V. 1 (25), pp. 39 – 46 (in
Ukrainian) (2013)
[20] Shustov, M.A.: Reversivnaya rabota logicheskih elementov. In: RadioLotsman, V. 08, pp. 44 –
46 (in Russian) (2019)
[21] Liu, L., Wang, D., Wang, Y., Lansner, A., Hemani, A., Yang, Y., Hu, X., Zou, Z., Zheng, L.: A
FPGA-based Hardware Accelerator for Bayesian Confidence Propagation Neural Network. In:
Nordic Circuits and Systems Conference (NorCAS) 2020 IEEE, pp. 1 – 6 (2020)