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Titlebook: Unconventional Computation and Natural Computation; 13th International C Oscar H. Ibarra,Lila Kari,Steffen Kopecki Conference proceedings 2

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31#
發(fā)表于 2025-3-27 00:42:03 | 只看該作者
32#
發(fā)表于 2025-3-27 03:14:32 | 只看該作者
33#
發(fā)表于 2025-3-27 05:52:05 | 只看該作者
34#
發(fā)表于 2025-3-27 09:49:00 | 只看該作者
Dynamic Adaptive Neural Network Array,ent programmability, how the dynamic components of a neuron and synapse are supported, and the structure used to support the monitoring and control interface. Finally, we present initial results from simulations of the hardware, the projected performance of the array elements and the physical implementation of a DANNA on a Xilinx FPGA.
35#
發(fā)表于 2025-3-27 14:18:16 | 只看該作者
Producibility in Hierarchical Self-assembly, shown that if two assemblies are producible, and if they can be overlapped consistently – i.e., if the positions that they share have the same tile type in each assembly – then their union is also producible.
36#
發(fā)表于 2025-3-27 18:06:52 | 只看該作者
37#
發(fā)表于 2025-3-28 01:17:26 | 只看該作者
An Energy-Efficient Computing Approach by Filling the Connectome Gap, the computing process and data with the control processes when achieving energy-efficient computing for large-scale cognitive computing tasks. The use of freespace optics is proposed as a means to efficiently handle sparse but still heavily entangled connections.
38#
發(fā)表于 2025-3-28 03:15:28 | 只看該作者
0302-9743 CNC 2014, held in London, ON, Canada, in July 2014. The 31 revised full papers were carefully reviewed and selected from 79 submissions. The papers cover a wide range of topics including among others molecular, quantum, optical and chaos computing as well as neural computation, evolutionary computat
39#
發(fā)表于 2025-3-28 09:17:26 | 只看該作者
40#
發(fā)表于 2025-3-28 12:30:24 | 只看該作者
Towards an MP Model for B Lymphocytes Maturation,vivo) data, and a preliminary model to explain the eight statistically refined time series, which opened up interesting questions about network inference and methodologies to analyze cross sectional data.
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