RESUMEN
Neuromorphic computing research is being actively pursued to address the challenges posed by the need for energy-efficient processing of big data. One of the promising approaches to tackle the challenges is the hardware implementation of spiking neural networks (SNNs) with bio-plausible learning rules. Numerous research works have been done to implement the SNN hardware with different synaptic plasticity rules to emulate human brain operations. While a standard spike-timing-dependent-plasticity (STDP) rule is emulated in many SNN hardware, the various STDP rules found in the biological brain have rarely been implemented in hardware. This study proposes a CMOS-memristor hybrid synapse circuit for the hardware implementation of a Ca ion-based plasticity model to emulate the various STDP curves. The memristor was adopted as a memory device in the CMOS synapse circuit because memristors have been identified as promising candidates for analog non-volatile memory devices in terms of energy efficiency and scalability. The circuit design was divided into four sub-blocks based on biological behavior, exploiting the non-volatile and analog state properties of memristors. The circuit was designed to vary weights using an H-bridge circuit structure and PWM modulation. The various STDP curves have been emulated in one CMOS-memristor hybrid circuit, and furthermore a simple neural network operation was demonstrated for associative learning such as Pavlovian conditioning. The proposed circuit is expected to facilitate large-scale operations for neuromorphic computing through its scale-up.
RESUMEN
This study evaluated arterial wall stiffness independent of variant background blood pressure. A new technique-arterial wall stiffness index (AWSI)-was developed and its use verified. Intraluminal pressure and luminal volume were measured on eight swine descending aortas. AWSI was formulated to evaluate absolute arterial wall stiffness independent of variable blood pressure and aortic size. AWSI variability with pressure change was compared with other wall stiffness evaluation parameters. AWSI determined from 100 descending aortic cine CT images and 108 carotid artery ultrasonography datasets were compared with age and Framingham risk score, respectively. Between 50 and 360 mmHg blood pressures, AWSI variance was 5.43% compared to 64.99% for classical compliance. AWSI correlated better with Framingham risk score and age than conservative wall stiffness evaluation methods. AWSI is a suitable method to evaluate arterial wall properties independent of variable background blood pressure and aortic size effects.