Functional model of biological neural networks

A Low-Order Model of Biological Neural Networks

A biologically plausible low-order model (LOM) of biological neural networks is proposed. LOM is a recurrent hierarchical network of models of dendritic nodes and trees; spiking and nonspiking neurons; unsupervised, supervised covariance and accumulative learning mechanisms; feedback connections; and a scheme for maximal generalization. These component models are motivated and necessitated by m...

Simulation of Biological Neural Networks

The list of success stories of the use of mathematics and mathematical simulation in physics, chemistry and engineering is endless. In the biological sciences the situation is different. The training of students in biology or medicine traditionally puts little emphasis on mathematics and physics, and skepticism towards any benefits of mathematics in describing living systems prevails in the bio...

rodbar dam slope stability analysis using neural networks

در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...

Biological Learning in Neural Networks

Neural Networks and Biological Modeling

is the jacobian matrix of F . If this matix has n distinct eigenvalues λk (real or complex), the system can be diagonalized, and the solutions can be expressed as combinations of exponentials of the form ek. Therefore, x − x∗ → 0 if all the eigenvalues have a negative real part. If one or more eigenvalues have positive real part, |x− x∗| → ∞. Therefore, • The fixed point x∗ is stable if all the...