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Therefore, in this paper, we present a probability density computing neural network (NN) training procedure. To overcome the limitation of an effective cost function, example uncertainty bounds are ...

Additive Noise,Bit Error,Bit Error Rate,Coupling Values,Decision Threshold,Discrete Function,Dominant Noise,Error Probability,Gaussian Assumption,Load Threshold ...

An example of dependent events is a company's stock price increasing after the company reports higher-than-expected earnings. If events are independent, then the probability of event B occurring ...

Due to its complex geometrical configuration, a SC-SPET system’s response matrix comprises of individual components, i.e. projection probability density functions (PPDFs), with variable spatial ...

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This valuable study investigates how stochastic and deterministic factors are integrated during cellular decision-making, particularly in situations where cells differentiate into distinct fates ...

The unfolded protein response (UPR) is a crucial signaling network that preserves endoplasmic reticulum (ER) homeostasis, impacting both health and disease. When ER stress occurs, often due to an ...

The surge in the global population, coupled with increasing urbanization, lays the foundation for the greenhouse film market’s robust growth. Urbanization brings about a shift in the demand for ...

Although the world has largely moved on from Covid-19, a lot of trust was destroyed including – unfortunately and worryingly ...