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Runs several simulations and returns output activation for each simulation and each input pattern
run_sim( patterns, frequency, duration, lrate_onset, lrate_drop_time, lrate_drop_perc, n_runs = 100, n_output_units = ncol(patterns), pulses_per_second = 1 )
matrix with input patterns, one row is one pattern
presentation frequency for each pattern in the matrix
presentation duration for each pattern in the matrix
learning rate at the onset of a stimulus
point at which the learning rate drops, must be lower than duration
how much the learning rate drops at lrate_drop_time
number of simulations to be run, default is 100
number of output units, defaults to number of input units
how many time steps should be simulated per second
list with following elements
output: the sum of the activation strengths of the output units for each input pattern
weight_matrix: final weight_matrix
pres_matrix: presentation matrix
run_exp
# NOT RUN { run_sim(diag(10), 1:10, 10:1, 0.05, 2, 0.2) # }
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