**IAF Encoding**(`iaf_encode.m`

) [2] [11]:Encodes a time-varying signal using an IAF neuron. Leaky and ideal neuron models are supported. In addition, IAF neuron with random (Gaussian) thresholds is also supported. A signal can be encoded by a single IAF encoder (Single-Input Single-Output Encoding), as shown in the figure below, or it can be encoded by a population of IAF neurons (Single-Input Multi-Output Encoding).

**ON-OFF IAF Encoding**(`iaf_encode_ideal_on_off.m`

) [12]:Encodes a time-varying signal using an ON-OFF IAF neuron pair. Only ideal IAF neuron models are supported.

**Decoding**(`iaf_decode.m`

) [1]:Reconstructs a bandlimited signal encoded by an IAF neuron using sinc kernels.

**Decoding using Fast Approximation Method**(`iaf_decode_fast.m`

) [4]:Reconstructs a bandlimited signal encoded by an IAF neuron using a fast approximation method.

**Decoding using Spline Interpolation**(`consistent_decoding_LIF.m`

) [12]:Reconstructs a finite-energy signal encoded by an Leaky-Integrate-and-Fire (LIF) neuron. It uses spline interpolation algorithm.

**Decoding using Smoothing Spline**(`LIF_decode_S1.m`

,`LIF_decode_S2.m`

) [11]:Reconstructs a signal in Sobolev space or encoded by a LIF neuron using smoothing splines. Signals encoded by a LIF with random threshold should be decoded using this function.

**Decoding for ON-OFF IAF**(`consistent_decoding_IF_ONOFF.m`

) [12]:Reconstructs a finite energy signal encoded by ON-OFF IAF neuron pair. The reconstruction is performed using spline interpolation method.

**Population Decoding**(`iaf_decode_pop.m`

) [7]:Reconstructs a bandlimited signal encoded by an ensemble of IAF neurons using sinc kernels.

**Population Decoding using Smoothing Splines**(`LIF_pop_decode_S1.m`

,`LIF_pop_decode_S2.m`

) [11]:Reconstructs a signal in Sobolev Space or encoded by a population of LIF neurons. The reconstruction uses smoothing spline method in the RKHS. Signals encoded by population of LIF with random threshold should be decoded using this function.

**Population Decoding using Spline Interpolation**(`consistent_decoding_IF_MIMO.m`

) [12]:Reconstructs multiple finite energy signals encoded by a population of ideal IAF neurons in Multiple-Input Multiple Output setting. The reconstruction uses spline interpolation method.