Method and apparatus for adaptive signal processing
A method for adaptive signal processing is provided. In the method, a second vector is obtained by initializing a first vector without regularization of a cost function. The cost function is regularized with the first vector and the second vector as variables. The first vector is updated based on an input signal, according to the regularized cost function. Then, an output signal is provided based on the updated first vector. The second vector is updated based on the update of the first vector. An apparatus for adaptive signal processing is provided accordingly. The method and the apparatus are well compatible with existing adaptive signal processing. The convergence coefficients of the adaptive filter system become more stable. Moreover, impact of an extra penalty added to the cost function on a bias can be minimized, and the increased complexity of the system is very limited.
1. A method for adaptive signal processing, comprising:
obtaining a second vector by initializing a first vector without regularization of a cost function;
regularizing the cost function with the first vector and the second vector as variables;
updating the first vector based on an input signal, according to the regularized cost function;
providing an output signal based on the updated first vector; and
updating the second vector based on the update of the first vector.
2. The method of claim 1 , wherein the obtaining of the second vector further comprises:
converging the first vector based on an input signal; and
configuring the second vector as a value of the first vector when convergence of the first vector fulfills a predetermined criterion.
3. The method of claim 1 , wherein the updating of the first vector further comprises:
taking a gradient of the regularized cost function; and
configuring the first vector based on the gradient.
4. The method of claim 1 , wherein the second vector is updated every predetermined number of iterations of updating the first vector.
5. The method of claim 1 , wherein the second vector is updated using a soft update.
6. The method of any of claim 1 , wherein the method is performed in an adaptive filter.
7. An apparatus for adaptive signal processing, comprising:
a processor; and
a memory communicatively coupled to the processor and adapted to store instructions which, when executed by the processor, cause the apparatus to perform operations of:
obtaining a second vector by initializing a first vector without regularization of a cost function;
regularizing the cost function with the first vector and the second vector as variables;
updating the first vector based on an input signal, according to the regularized cost function;
providing an output signal based on the updated first vector; and
updating the second vector based on the update of the first vector.
8. The apparatus of claim 7 , wherein the instructions, when executed by the processor, cause the apparatus to initialize the first vector by:
converging the first vector based on an input signal; and
configuring the second vector as a value of the first vector when convergence of the first vector fulfills a predetermined criterion.
9. The apparatus of claim 7 , wherein the instructions, when executed by the processor, cause the apparatus to update the first vector by:
taking a gradient of the regularized cost function; and
configuring the first vector based on the gradient.
10. The apparatus of claim 7 , wherein the second vector is updated every predetermined number of iterations of updating the first vector.
11. The apparatus of claim 7 , wherein the second vector is updated using a soft update.
12. The apparatus of claim 7 , wherein the apparatus is implemented in an adaptive filter.
13. A non-transitory computer readable medium having a computer program stored thereon which, when executed by a set of one or more processors of an apparatus, causes the apparatus to perform:
obtaining a second vector by initializing a first vector without regularization of a cost function;
regularizing the cost function with the first vector and the second vector as variables;
updating the first vector based on an input signal, according to the regularized cost function;
providing an output signal based on the updated first vector; and
updating the second vector based on the update of the first vector.