sPyNNaker neural_modelling 7.1.1
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threshold_type_none.h
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1/*
2 * Copyright (c) 2017 The University of Manchester
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * https://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
19#ifndef _THRESHOLD_TYPE_NONE_H_
20#define _THRESHOLD_TYPE_NONE_H_
21
22#include "threshold_type.h"
23
25};
26
27struct threshold_type_t {
28};
29
30static void threshold_type_initialise(UNUSED threshold_type_t *state,
31 UNUSED threshold_type_params_t *params, UNUSED uint32_t n_steps_per_timestep) {
32}
33
34static void threshold_type_save_state(UNUSED threshold_type_t *state,
36}
37
43 UNUSED state_t value, UNUSED threshold_type_t *threshold_type) {
44 return 0;
45}
46
47#endif // _THRESHOLD_TYPE_NONE_H_
REAL state_t
The type of a state variable.
static uint n_steps_per_timestep
The number of steps to run per timestep.
static stdp_params params
Configuration parameters.
API for threshold types.
static bool threshold_type_is_above_threshold(state_t value, threshold_type_t *threshold_type)
Determines if the value given is above the threshold value.
Stochastic threshold parameters.
Stochastic threshold configuration.