Biological systems are energy efficient in their information processing. These systems use techniques different from conventional artificial electronic systems to achieve this. Concepts found in in neurobiological systems can be exploited to build faster, more energy efficient and robust electronic systems. It also seems possible that these concepts can be replicated on silicon. Properties and concepts of neural systems are discussed here to give the basic understanding of these systems and possibilities there are in making use of them. Also link between Shannon's Theorem and biological information processing is shortly discussed
Neuromorphic systems emulate the organization and function of nervous systems. They are usually comp...
Artificial neural networks (ANNs) and computational neuroscience models have made tremendous progres...
A SUMMARY The von Neumann computing architecture consists of separated processing and memory element...
Neural systems found in the brains of even very simple animals are amazingly effective at performing...
Neuromorphic engineering attempts to understand the computational properties of neural processing sy...
Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techni...
Today software systems known as neural networks are at the basis of numerous artificial intelligence...
In attempting to understand neurobiological computation, it is natural to apply − or try to apply − ...
International audienceCurrent classical computers are playing a critical role in advanced research s...
Many of the current artificial intelligence (AI) applications that are rapidly becoming indispensabl...
International audienceIn a context of the end of Moore's law, energy dissipation constitutes a real ...
The human brain efficiently processes information by analog integration of inputs and digital, binar...
In systems biology, questions concerning the molecular and cellular makeup of an organism are of utm...
The brain is the most complex computational machine known to science, even though its components (ne...
In systems biology, questions concerning the molecular and cellular makeup of an organism are of utm...
Neuromorphic systems emulate the organization and function of nervous systems. They are usually comp...
Artificial neural networks (ANNs) and computational neuroscience models have made tremendous progres...
A SUMMARY The von Neumann computing architecture consists of separated processing and memory element...
Neural systems found in the brains of even very simple animals are amazingly effective at performing...
Neuromorphic engineering attempts to understand the computational properties of neural processing sy...
Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techni...
Today software systems known as neural networks are at the basis of numerous artificial intelligence...
In attempting to understand neurobiological computation, it is natural to apply − or try to apply − ...
International audienceCurrent classical computers are playing a critical role in advanced research s...
Many of the current artificial intelligence (AI) applications that are rapidly becoming indispensabl...
International audienceIn a context of the end of Moore's law, energy dissipation constitutes a real ...
The human brain efficiently processes information by analog integration of inputs and digital, binar...
In systems biology, questions concerning the molecular and cellular makeup of an organism are of utm...
The brain is the most complex computational machine known to science, even though its components (ne...
In systems biology, questions concerning the molecular and cellular makeup of an organism are of utm...
Neuromorphic systems emulate the organization and function of nervous systems. They are usually comp...
Artificial neural networks (ANNs) and computational neuroscience models have made tremendous progres...
A SUMMARY The von Neumann computing architecture consists of separated processing and memory element...