diff --git a/js/ml/HiddenLayer.js b/js/ml/HiddenLayer.js
new file mode 100644
index 0000000..59892c9
--- /dev/null
+++ b/js/ml/HiddenLayer.js
@@ -0,0 +1,59 @@
+/**
+ * Created by joonkukang on 2014. 1. 12..
+ */
+var math = Require('ml/math');
+var HiddenLayer = module.exports = function (settings) {
+    var L = {}
+    var self = L;
+    self.input = settings['input'];
+
+    if(typeof settings['W'] === 'undefined') {
+        var a = 1. / settings['n_in'];
+        settings['W'] = math.randMat(settings['n_in'],settings['n_out'],-a,a);
+    }
+    if(typeof settings['b'] === 'undefined')
+        settings['b'] = math.zeroVec(settings['n_out']);
+    if(typeof settings['activation'] === 'undefined')
+        settings['activation'] = math.sigmoid;
+
+    self.W = settings['W'];
+    self.b = settings['b'];
+    self.activation = settings['activation'];
+    return L;
+}
+
+HiddenLayer.code = {
+  output : function(L,input) {
+    var self = L;
+    if(typeof input !== 'undefined')
+        self.input = input;
+
+    var linearOutput = math.addMatVec(math.mulMat(self.input,self.W),self.b);
+    return math.activateMat(linearOutput,self.activation);
+  },
+  linearOutput : function(L,input) { // returns the value before activation.
+    var self = L;
+    if(typeof input !== 'undefined')
+        self.input = input;
+
+    var linearOutput = math.addMatVec(math.mulMat(self.input,self.W),self.b);
+    return linearOutput;
+  },
+  backPropagate : function (L,input) { // example+num * n_out matrix
+    var self = L;
+    if(typeof input === 'undefined')
+        throw new Error("No BackPropagation Input.")
+
+    var linearOutput = math.mulMat(input, math.transpose(self.W));
+    return linearOutput;
+  },
+  sampleHgivenV : function(L,input) {
+    var self = L;
+    if(typeof input !== 'undefined')
+        self.input = input;
+
+    var hMean = HiddenLayer.code.output(self);
+    var hSample = math.probToBinaryMat(hMean);
+    return hSample;
+  }
+}