/*public vNeuron(main.Network inNet, List<List<int>> inInputNs, int inLayer, int inDim) * { * this.inputNeurons = inInputNs; * this.layer = inLayer; * this.dimension = inDim; * * this.weights = new List<List<double>>(); * for(int i = 0; i < inNet.NUM_DEPTH; i++) * { * this.weights.Add(Enumerable.Repeat(DEFAULT_WEIGHT, inDim).ToList()); * } * }*/ //Input Neuron Constructor public vNeuron(List <double> output) { this.layer = 0; this.actFunc = actFuncType.identity; this.dimension = output.Count; this.inputs.Add(new List <double>()); for (int i = 0; i < this.dimension; i++) { this.inputs[0].Add(output[i]); this.beta.Add(0d); } this.weights.Add(MyMath.makeIdentityMatrix(this.dimension)); }
//Input Neuron Constructor public mNeuron(List <List <double> > output) { this.layer = 0; this.actFunc = actFuncType.identity; int d = 0; this.inputs.Add(new List <List <double> >()); for (int i = 0; i < output.Count; i++) { d++; this.inputs[0].Add(new List <double>()); this.beta.Add(new List <double>()); for (int j = 0; j < output[0].Count; j++) { this.inputs[0][i].Add(output[i][j]); this.beta[i].Add(0d); } } this.weights.Add(MyMath.makeIdentityMatrix(d)); }