first commit

source/decompiled/de/maxhenkel/voicechat/concentus/MultiLayerPerceptron.java

@@ -0,0 +1,61 @@
+/*
+ * Decompiled with CFR 0.152.
+ */
+package de.maxhenkel.voicechat.concentus;
+
+import de.maxhenkel.voicechat.concentus.MLPState;
+import de.maxhenkel.voicechat.concentus.OpusTables;
+
+class MultiLayerPerceptron {
+    private static final int MAX_NEURONS = 100;
+
+    MultiLayerPerceptron() {
+    }
+
+    static float tansig_approx(float x) {
+        float sign = 1.0f;
+        if (!(x < 8.0f)) {
+            return 1.0f;
+        }
+        if (!(x > -8.0f)) {
+            return -1.0f;
+        }
+        if (x < 0.0f) {
+            x = -x;
+            sign = -1.0f;
+        }
+        int i = (int)Math.floor(0.5f + 25.0f * x);
+        float y = OpusTables.tansig_table[i];
+        float dy = 1.0f - y * y;
+        y += (x -= 0.04f * (float)i) * dy * (1.0f - y * x);
+        return sign * y;
+    }
+
+    static void mlp_process(MLPState m, float[] input, float[] output) {
+        int k;
+        float sum;
+        int j;
+        float[] hidden = new float[100];
+        float[] W = m.weights;
+        int W_ptr = 0;
+        for (j = 0; j < m.topo[1]; ++j) {
+            sum = W[W_ptr];
+            ++W_ptr;
+            for (k = 0; k < m.topo[0]; ++k) {
+                sum += input[k] * W[W_ptr];
+                ++W_ptr;
+            }
+            hidden[j] = MultiLayerPerceptron.tansig_approx(sum);
+        }
+        for (j = 0; j < m.topo[2]; ++j) {
+            sum = W[W_ptr];
+            ++W_ptr;
+            for (k = 0; k < m.topo[1]; ++k) {
+                sum += hidden[k] * W[W_ptr];
+                ++W_ptr;
+            }
+            output[j] = MultiLayerPerceptron.tansig_approx(sum);
+        }
+    }
+}
+