Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Neural codingNeural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble. Based on the theory that sensory and other information is represented in the brain by networks of neurons, it is thought that neurons can encode both digital and analog information.
Magnocellular neurosecretory cellMagnocellular neurosecretory cells are large neuroendocrine cells within the supraoptic nucleus and paraventricular nucleus of the hypothalamus. They are also found in smaller numbers in accessory cell groups between these two nuclei, the largest one being the circular nucleus. There are two types of magnocellular neurosecretory cells, oxytocin-producing cells and vasopressin-producing cells, but a small number can produce both hormones. These cells are neuroendocrine neurons, are electrically excitable, and generate action potentials in response to afferent stimulation.
Supraoptic nucleusThe supraoptic nucleus (SON) is a nucleus of magnocellular neurosecretory cells in the hypothalamus of the mammalian brain. The nucleus is situated at the base of the brain, adjacent to the optic chiasm. In humans, the SON contains about 3,000 neurons. The cell bodies produce the peptide hormone vasopressin, which is also known as anti-diuretic hormone (ADH), and the peptide hormone oxytocin. Both of these peptides are released from the posterior pituitary.
Functional verificationFunctional verification is the task of verifying that the logic design conforms to specification. Functional verification attempts to answer the question "Does this proposed design do what is intended?" This is complex and takes the majority of time and effort (up to 70% of design and development time) in most large electronic system design projects. Functional verification is a part of more encompassing design verification, which, besides functional verification, considers non-functional aspects like timing, layout and power.
