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Noise immunity of oscillatory computing devices

Gyorgy Csaba, Wolfgang Porod
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/564zgfphebbivd6ewps35rlq2m" style="color: black;">IEEE Journal on Exploratory Solid-State Computational Devices and Circuits</a> </i> &nbsp;
The computational model of a Hopfield network is implemented using both level-and phase-based signal representations, and these models are simulated assuming both 1/f and thermal noise.  ...  INDEX TERMS Artificial neural networks, circuit noise, Hopfield neural networks, ring oscillators (ROs).  ...  [Norwegian University of Science and Technology (NTNU)] for valuable discussions regarding circuit design.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jxcdc.2020.3046558">doi:10.1109/jxcdc.2020.3046558</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3eg6ya3b7ze7dar5frbxukiis4">fatcat:3eg6ya3b7ze7dar5frbxukiis4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429160104/https://ieeexplore.ieee.org/ielx7/6570653/9347845/09302732.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/87/d1/87d178d0a5b6692105fd3e09a162d8d319789a45.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jxcdc.2020.3046558"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

A COMPENSATED FUZZY HOPFIELD NEURAL NETWORK FOR CODEBOOK DESIGN IN VECTOR QUANTIZATION

SHAO-HAN LIU, JZAU-SHENG LIN
<span title="">2000</span> <i title="World Scientific Pub Co Pte Lt"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ctczi3cdmjfarjhjbdobmuwpkm" style="color: black;">International journal of pattern recognition and artificial intelligence</a> </i> &nbsp;
In this paper, a new Hopfield-model net called Compensated Fuzzy Hopfield Neural Network (CFHNN) is proposed for vector quantization in image compression.  ...  The training vectors on a divided image are mapped to a two-dimensional Hopfield neural network.  ...  of Technology, Taichung, Taiwan, R.O.C.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1142/s0218001400000647">doi:10.1142/s0218001400000647</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g4xhsdzli5drffszp6lhm4vlli">fatcat:g4xhsdzli5drffszp6lhm4vlli</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721231326/http://140.128.95.1/bitstream/987654321/2000/1/2000-a" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/77/44/7744c6468a5bd929385a01bbed0d4b67f83ecd37.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1142/s0218001400000647"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> worldscientific.com </button> </a>

Dynamical Nonlinear Neural Networks with Perturbations Modeling and Global Robust Stability Analysis

Gamal A.Elnashar
<span title="2014-01-16">2014</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
Keywords Perturbed nonlinear systems, Hopfield neural network, Lyapunov stability, equilibrium state    makes up the interconnections between the th i neuron and the remaining neurons in the network  ...  A kind of Lyapunov's stability of the stable points of Hopfield neural network (HNN) have been proven, which means that if the initial state of the network is close enough to a stable point, then the network  ...  STABILITY ANALYSIS OF HOPFIELD NEURAL NETWORK Lyapunov's second method in conjunction with interconnection information will now be used in the stability analysis of the Hopfield neural model viewed as  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/14917-3479">doi:10.5120/14917-3479</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bearq3qewbedfgulculu7arcny">fatcat:bearq3qewbedfgulculu7arcny</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180603031045/https://research.ijcaonline.org/volume85/number15/pxc3893479.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/21/9e/219e835b91a295a3307903d72f04db47c29b492e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/14917-3479"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Correlating matched-filter model for analysis and optimisation of neural networks

D.R. Selviah, J.E. Midwinter, A.W. Rivers, K.W. Lung
<span title="">1989</span> <i title="Institution of Engineering and Technology (IET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/7mrikjgjyvafbduz4rfrgttzq4" style="color: black;">IEE Proceedings F Radar and Signal Processing</a> </i> &nbsp;
The procedure is demonstrated on the synchronous Little-Hopfield network.  ...  The most efficient convergence of the synchronous Little-Hopfield net is obtained when the neurons are connected to themselves with a weight equal to the number of stored codes.  ...  Acknowledgment The authors wish to express their grateful thanks to Dr. M. Shirivani, Prof. P.M. Grant  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/ip-f-2.1989.0024">doi:10.1049/ip-f-2.1989.0024</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p2gakhctgzaglbgeqgjhwozz6y">fatcat:p2gakhctgzaglbgeqgjhwozz6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170923015825/http://discovery.ucl.ac.uk/2666/1/2666.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fe/5b/fe5b18a8f5fbe037d7164c9b761a784097514550.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/ip-f-2.1989.0024"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Pattern recognition in Hopfield type networks with a finite range of connections

Eva Koscielny-Bunde
<span title="">1990</span> <i title="EDP Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xwajwmvtdre3np2er6u3abo444" style="color: black;">Journal de Physique</a> </i> &nbsp;
The solution could be achieved since all neurons in the net are interconnected.  ...  the conventional Hopfield net The result is plotted versus Mlz rather than MIN.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/jphys:0199000510170179700">doi:10.1051/jphys:0199000510170179700</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/t65f64kmmvhvbcb6kjgddt3daa">fatcat:t65f64kmmvhvbcb6kjgddt3daa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170927133541/https://hal.archives-ouvertes.fr/jpa-00212491/document" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bf/a2/bfa2db356bb96ff352e5005e1735fbc7d849c0f3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/jphys:0199000510170179700"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

The Computational Power of Discrete Hopfield Nets with Hidden Units

Pekka Orponen
<span title="1996-02-15">1996</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Every two consecutive layers of wires are interconnected by an intermediate layer of q(n) constant-size subcircuits, each implementing the local transition rule of machine M at a single position of the  ...  When no restrictions are placed on either computation time or the sizes of interconnection weights, both of these classes of networks compute ex- actly the class of functions PSPACE/poly.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.1996.8.2.403">doi:10.1162/neco.1996.8.2.403</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/end5lj6yzbhmzi5yzxsk7tv7my">fatcat:end5lj6yzbhmzi5yzxsk7tv7my</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/details/sim_neural-computation_1996-03-15_8_2/page/403" title="read fulltext microfilm" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Archive [Microfilm] <div class="menu fulltext-thumbnail"> <img src="https://archive.org/serve/sim_neural-computation_1996-03-15_8_2/__ia_thumb.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.1996.8.2.403"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Existence and stability of a unique equilibrium in continuous-valued discrete-time asynchronous Hopfield neural networks

A. Bhaya, E. Kaszkurewicz, V.S. Kozyakin
<span title="">1996</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/22mhkeaq5zdqlmtti5oidj26fi" style="color: black;">IEEE Transactions on Neural Networks</a> </i> &nbsp;
It is shown that the assumption of D-stability of the interconnection matrix, together with the standard assumptions on the activation functions, guarantee a unique equilibrium under a synchronous mode  ...  Second, using results of Bhaya and coworkers, it is shown that, under the standard assumptions, if the nonnegative matrix whose elements are the absolute values of the corresponding elements of the interconnection  ...  local or global, depending on the strength of the condition imposed on the interconnection matrix; and (iii) it is possible to quantify a bound on desymmetrizing perturbations (on the nominal symmetric  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/72.501720">doi:10.1109/72.501720</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18263459">pmid:18263459</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fgp5fyirxrdjbndgbgsn5a7lka">fatcat:fgp5fyirxrdjbndgbgsn5a7lka</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190226195438/http://pdfs.semanticscholar.org/7677/3d28230e832b143fa31740533c9f726be18f.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/76/77/76773d28230e832b143fa31740533c9f726be18f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/72.501720"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Page 1643 of Neural Computation Vol. 8, Issue 8 [page]

<span title="1996-11-15">1996</span> <i title="MIT Press Journals"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_neural-computation" style="color: black;">Neural Computation </a> </i> &nbsp;
The capability of the low-dimensional model to approximate higher-dimensional models accurately makes it useful for describing complex dynamics of nets of interconnected neurons.  ...  The fast response of the activity vari- able also makes it possible to reduce the model to a one-dimensional model, in particular for typical conditions.  ... 
<span class="external-identifiers"> </span>
<a target="_blank" rel="noopener" href="https://archive.org/details/sim_neural-computation_1996-11-15_8_8/page/1643" title="read fulltext microfilm" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Archive [Microfilm] <div class="menu fulltext-thumbnail"> <img src="https://archive.org/serve/sim_neural-computation_1996-11-15_8_8/__ia_thumb.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a>

A high-speed neural analog circuit for computing the bit-level transform image coding

P.R. Chang, K.S. Hwang, H.M. Gong
<span title="">1991</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lfjucyeexrd75hshl2cngz7doq" style="color: black;">IEEE transactions on consumer electronics</a> </i> &nbsp;
A novel Hopfield-type neural net with a number of graded-response neurons designed to perform the quadratic nonlinear programming would lead to such a solution in a time determined by RC time constants  ...  In order to utilize the concept of neural net, the computation of a two-dimensional DCT-based transform coding should be reformulated as minimizing a quadratic nonlinear programming problem subject to  ...  The overall output of the p t h vector multiplier, u t ) is given = the constant depends on the characteristics of MOS implementation.It is interesting to note that the constant c could be compensated  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/30.85534">doi:10.1109/30.85534</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/avipybb7pnhbzldlokmpxamkma">fatcat:avipybb7pnhbzldlokmpxamkma</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813043504/https://ir.nctu.edu.tw/bitstream/11536/3715/1/A1991GE54700025.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c9/e9/c9e9e1373c5dcb66781c37f249cf3a0f512a43d8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/30.85534"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Compact analogue neural network: a new paradigm for neural based combinatorial optimisation

Jayadeva, S.C. Dutta Roy, A. Chaudhary
<span title="">1999</span> <i title="Institution of Engineering and Technology (IET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/p4qo74anhjb3bffx42h3l6ve5y" style="color: black;">IEE Proceedings - Circuits Devices and Systems</a> </i> &nbsp;
to the Hopfield net.  ...  In contrast, a Hopfield net would require N 2 neurons and 0{N*) interconnection weights.  ...  In their papers in the 1980s, Hopfield and Tank [1, 2] showed that a coupled system of neurons, now well known as the 'Hopfield net', converges to a local minimum of an associated energy function.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/ip-cds:19990314">doi:10.1049/ip-cds:19990314</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rotmz4kkd5d3pgo5orrbb4xjfu">fatcat:rotmz4kkd5d3pgo5orrbb4xjfu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170921215136/http://eprint.iitd.ac.in/bitstream/2074/1972/1/jayadevacom1999.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bb/68/bb68291728a26f3683923c0cc88918c711172a49.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1049/ip-cds:19990314"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Artificial Neural Networks and Hopfield Type Modeling

Haydar Akca
<span title="2020-03-10">2020</span> <i title="Iris Publishers LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/w2jy3mli2vaqvcjy7cjfffp64y" style="color: black;">Global Journal of Engineering Sciences</a> </i> &nbsp;
classes of Hopfield neural networks modeling using functional differential equations in the presence of delay, periodicity, impulses and finite distributed delays.  ...  In the present talk, we briefly summarized historical background as well as developments of the artificial neural networks and present recent formulations of the continuous and discrete counterpart of  ...  Conflict of Interest No conflict of interest.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33552/gjes.2020.05.000601">doi:10.33552/gjes.2020.05.000601</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dqygg4t2sreohjolix2ujt73ee">fatcat:dqygg4t2sreohjolix2ujt73ee</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211011135611/https://irispublishers.com/gjes/pdf/GJES.MS.ID.000601.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/41/e5/41e51527341b46113ec0d5ce70019c46564383dc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.33552/gjes.2020.05.000601"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Recurrent Neural Networks: Associative Memory and Optimization

K. -L. Du
<span title="">2011</span> <i title="OMICS Publishing Group"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3vq4nfyo65gndle6y4jboqa4oy" style="color: black;">Journal of Information Technology &amp; Software Engineering</a> </i> &nbsp;
It is shown in [109] that the Hebbian rule is the zeroth-order expansion of the pseudoinverse rule, and the improved Hebbian rule given by (15) and (16) is one form of the first-order expansion of the  ...  For some RNN models such as the Hopfield model and the Boltzmann machine, the fixed-point property of the dynamic systems can be used for optimization and associative memory.  ...  Adjacent cells are connected by mutual interconnections [21, 22] . Each cell has its own dynamics whose evolution is dependent on its circuit time constant = RC τ .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4172/2165-7866.1000104">doi:10.4172/2165-7866.1000104</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zqfpc2fpwzhufigwozssmylotu">fatcat:zqfpc2fpwzhufigwozssmylotu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170813112112/https://www.omicsgroup.org/journals/recurrent-neural-networks-associative-memory-and-optimization-2165-7866.1000104.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e8/6d/e86dcad8c96d0d09b9e7378fef67e3feaf7c7226.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4172/2165-7866.1000104"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Page 407 of Neural Computation Vol. 8, Issue 2 [page]

<span title="1996-03-15">1996</span> <i title="MIT Press Journals"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_neural-computation" style="color: black;">Neural Computation </a> </i> &nbsp;
Every two consecutive layers of wires are interconnected by an intermediate layer of q(n) constant-size subcircuits, each implementing the local transition rule of machine M at a single position of the  ...  The input x is entered to the circuit along input wires; the advice string f() appears as a constant input on another set of wires; and the output is read from the particular wire at the end of the circuit  ... 
<span class="external-identifiers"> </span>
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An Overview of Hopfield Network and Boltzmann Machine

Saratha Sathasivam, Abdu Masanawa Sagir
<span title="2014-12-30">2014</span> <i title="RAME Publishers"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ppdjwpmqabhrpfr7v4kum24lem" style="color: black;">International journal of computational and electronics aspects in engineering</a> </i> &nbsp;
The two well-known and commonly used types of recurrent neural networks, Hopfield neural network and Boltzmann machine have different structures and characteristics.  ...  Neural networks are dynamic systems in the learning and training phase of their operations.  ...  ) for discrete Hopfield net is given by: E = −0.5 ∑ ∑ ≠ − ∑ + ∑ (3) -the threshold of unit i If the activation of the net changes by an amount∆y i , the energy changes by an amount ∆E = − [∑ + j x i −  ... 
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<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210806032110/https://www.rame.org.in/pdf/ijceae/volume1/issue1/vol1-issue1-ijceae20141205.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f7/64/f764321192e8ea1f50adcf51b7f77e8a62f85b5e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.26706/ijceae.1.1.20141205"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Response Characteristics of a Low-Dimensional Model Neuron

Bo Cartling
<span title="1996-11-15">1996</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Viewed as an extension of the most abstract models of Hopfield type, the present approach allows a description of more of the rich dynamics of nets of interconnected neu- rons.  ...  In models of nets of interconnected neurons, the low dimension of the model neuron becomes particularly important.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.1996.8.8.1643">doi:10.1162/neco.1996.8.8.1643</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/8888611">pmid:8888611</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6mk3j4j6zngq5eew6fb24dcqhu">fatcat:6mk3j4j6zngq5eew6fb24dcqhu</a> </span>
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