Sentence examples for memory signals from inspiring English sources

No theory of underlying memory signals (and no measure of d' m ) will change that fact.

A signal-detection-based theory about how the photos in a lineup generate memory signals makes a prediction about the degree to which memory signals for targets and foils overlap.

This measure is purely geometric and relies on no theoretical assumptions about the strengths of underlying memory signals.

Both were referring to what we have here denoted d' m (i.e., the degree to which the distributions of target and foil memory signals overlap).

Unlike policymakers, theoreticians seek to measure underlying latent variables like d' m (the degree to which memory signals overlap) and σ C (criterion variability).

One key issue on the magnetic memory method is to establish the quantitative relationship between the shape and size of defect and the surface magnetic memory signals.

Thus, a decision criterion must be set such that any memory signal that exceeds it yields a positive identification (ID), whereas any memory signal that falls below it results in a non-identification (No ID).

Increasing the CCF results in high raw BER (RBER) because the variance of Flash memory signal becomes larger.

For the Independent Observations model considered in the main text, the decision variable, f(x), is x1 itself (i.e., the untransformed MAX memory signal).

Recently Cohen and Grossberg neural networks [1] have been extensively studied and applied in many different fields such as associative memory, signal processing, and some optimization problems.

The memory signal associated with that face, which is not necessarily the MAX face in the lineup, determines the level of confidence.