Sentence examples for 1 neuron from inspiring English sources

Determined by previous tests, ANNs were structured with 14 neurons in the input layer (number of variables), 1 neuron in the hidden layer, and 1 neuron in the output layer, corresponding to estimated basal area or volume.

Several network architectures were tested to finally choose a three layer network with 6, 10 and 1 neuron, respectively (6, 10, 1).

The pair of neurons are parameterized so that Neuron 1 satisfies Case 1, Neuron 2 satisfies Case 2, and Lemma 1 holds.

The hidden layer having 5 neurons used a tangent sigmoid activation function (tansig) and lastly the output layer having 1 neuron used a linear activation function (purelin).

Each ANN has also 1 neuron in its output layer to predict the requested parameter based on the equations in Table 2.

A three-layer ANN was found to be optimum with architecture of 12 and 5 neurons in the first and second hidden layer, respectively, and 1 neuron in output layer.

A feed forward neural network based on back-propagation is a multilayered architecture made up of one or more hidden layers (2 layers–42 neurons) placed between the input (1 layer–5 neurons) and output (1 layer-1 neuron) layers.

The limitations of hiPSC-based approaches for studying psychiatric disease are mainly (1) neuron-to-neuron variability, (2) hiPSC-to-hiPSC variability and (3) patient-to-patient variability.

In this study we compared the diagnostic utility of: (1) neuron-specific enolase (NSE); (2) squamous cell carcinoma antigen (SCC); (3) carcinoembryonic antigen (CEA); and (4) cytokeratin markers (CYFRA 21-1, TPM, TPS, TPS) in patients with small-cell lung cancer (SCLC) (21 cases) and non-small-cell lung cancer (94 cases).

This conclusion is based on the observations that (1) neuron-specific Nf1Math1CKO cerebellum exhibited no such defect in the WM, and (2) Nf1-intact UBCs were arrested in the WM of the E17.5 TM-induced Nf1NCreERCKO cerebellum where excess astrocytes were present.

In addition, they still rely on the type-1 neuron, which has problems of uncertainty.