%?implementation?of?RNN?
clc
clear
close?all
%%?training?dataset?generation
binary_dim?=?8;

largest_number?=?2^binary_dim-1;
binary?=?cell（largest_number1）;
int2binary?=?cell（largest_number1）;
for?i?=?1:largest_number+1
????binary{i}?=?dec2bin（i-1?8）;
????int2binary{i}?=?binary{i};
end

%%?input?variables
alpha?=?0.1;
input_dim?=?2;
hidden_dim?=?16;
output_dim?=?1;

%%?initialize?neural?network?weights
synapse_0?=?2*rand（input_dimhidden_dim）?-?1;
synapse_1?=?2*rand（hidden_dimoutput_dim）?-?1;
synapse_h?=?2*rand（hidden_dimhidden_dim）?-?1;

synapse_0_update?=?zeros（size（synapse_0））;
synapse_1_update?=?zeros（size（synapse_1））;
synapse_h_update?=?zeros（size（synapse_h））;

%%?train?logic
for?j?=?0:19999
????%?generate?a?simple?addition?problem?（a?+?b?=?c）
??

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????5902??2018-10-11?17:19??RNN_matlab.m

-----------?---------??----------?-----??----

?????????????????5902????????????????????1