URL https://opencores.org/ocsvn/artificial_neural_network/artificial_neural_network/trunk

Subversion Repositories artificial_neural_network

[/] [artificial_neural_network/] [trunk/] [ANN_kernel/] [RTL_VHDL_files/] [activation_function.vhd] - Diff between revs 8 and 9

Rev 8	Rev 9
Line 40...	Line 40...
`);`	`);`
`end activation_function;`	`end activation_function;`

`architecture Structural of activation_function is`	`architecture Structural of activation_function is`

`component af_sigmoid is`
`generic`
`(`
`Nbit : natural := 8`
`);`
`port`
`(`
`reset : in std_logic;`
`clk : in std_logic;`
`run_in : in std_logic; -- Start and input data validation`
`inputs : in std_logic_vector(Nbit-1 downto 0); -- Input data`
`run_out : out std_logic; -- Output data validation, run_in for the next layer`
`outputs : out std_logic_vector(Nbit-1 downto 0) -- Output data`
`);`
`end component;`

`begin`	`begin`

`-- Linear activation function. It is a direct assignment:`	`-- Linear activation function. It is a direct assignment:`
`linear_f:`	`linear_f:`
`if (f_type = "linear") generate`	`if (f_type = "linear") generate`
Line 68...	Line 52...
`end generate;`	`end generate;`

`-- Example 1: sigmoid activation function implemented as a Look-Up-Table (LUT):`	`-- Example 1: sigmoid activation function implemented as a Look-Up-Table (LUT):`
`Sigmoid_f:`	`Sigmoid_f:`
`if (f_type = "siglut") generate`	`if (f_type = "siglut") generate`
`siglut_inst: af_sigmoid`	`siglut_inst: entity work.af_sigmoid`
`generic map`	`generic map`
`(`	`(`
`Nbit => Nbit`	`Nbit => Nbit`
`)`	`)`
`port map`	`port map`