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This suggests that the biophysical oscillatory behavior of neurons and synapses leads to selecting the corresponding frequency of the inputs and performing the same computation as for the Hebbian linear case of the previous section: computing the correlation of the (filtered) inputs.
Prior model publication in the statistics literature is not a sufficient indicator of a model's validity, and authors of modeling studies should be encouraged to take steps to increase the validity of their study by using systematically reviewed data inputs and performing sensitivity analyses and external validation.
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We engineer cells that can both sense desired ligand inputs and perform designed output functions.
The general model architecture they used is called a recurrent neural network: a set of software modules designed to accept inputs and perform tasks similar to how biological neurons operate.
Her lab is also developing new computing approaches inspired by decision-making processes in neural networks to allow molecular robots to respond to their environments, compute specific inputs, and perform varying tasks, such as recognizing patterns that contain 100 bits of information.
Foat et al. proposed MatrixREDUCE [ 17], a statistical mechanics method that took high-throughput measurements of binding affinity as inputs and performed a least-squares fit to estimate the position specific affinity matrix that contained the relative energy contribution of each nucleotide at different positions.
Taking advantage of the TRT library allowed us to separate the processes for receiving input and performing the movement adjustments.
The Commission has a robust process during rule adoption for obtaining public input and performing cost-benefit analysis, but should also review its rules retrospectively to find areas where they are not functioning as intended ("[w]e cannot be shy about being introspective and self-critical").
Chang and Lin [7] suggest choosing an initial set of possible input parameters and performing grid search cross-validation to find optimal (with respect to the given grid and the given search criterion) parameters for SVM, whereby cross-validation is used to select optimal tuning parameters from a one-dimensional or multi-dimensional grid.
One approach to resolve these questions involves generating artificial oscillations, without natural input signaling, and performing perturbation experiments in a genetically-targeted manner with spatiotemporal accuracy.
The constructional analyzer takes an utterance as input and performs deep semantic analysis, mapping the utterance onto its most likely interpretation.
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