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Paradigmas neurais quânticos e dinâmica de aprendizagem

Paradigmas neurais quânticos e dinâmica de aprendizagem

Ishwarya M. V. / Narayana K. E. / Prinslin L. L.

133,83 €
IVA incluido
Disponible
Editorial:
KS OmniScriptum Publishing
Año de edición:
2026
Materia
Empresa y gestión
ISBN:
9786209956379
133,83 €
IVA incluido
Disponible

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Sobre IBD

As redes neuronais, inspiradas nos sistemas neuronais biológicos, são constituídas por camadas interligadas de neurónios artificiais que processam e transmitem informações. Cada neurónio recebe sinais de entrada, aplica uma transformação e transmite o resultado às camadas seguintes. Através de um processo conhecido como treino, as redes neuronais ajustam os seus parâmetros internos para minimizar os erros e melhorar o desempenho em tarefas específicas. Esta capacidade de adaptação torna-as altamente eficazes em aplicações como o reconhecimento de imagens, o processamento de linguagem natural e a análise preditiva. A força das redes neuronais reside na sua capacidade de aprender padrões complexos a partir de dados, tornando-as ferramentas indispensáveis na inteligência artificial moderna.A integração da computação quântica e das redes neuronais é motivada pelas limitações das abordagens clássicas quando se trata de dados de elevada dimensão e de problemas de otimização complexos. As redes neuronais clássicas requerem recursos computacionais significativos para o treino, especialmente à medida que a dimensão da rede e o volume de dados aumentam.

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