# mach: bfin // GENERIC BIQUAD: // --------------- // x ---------+---------|---------+-------y // | |t1 | // | D | // | a1 | b1 | // +---<-----|---->----+ // | | | // | D | D's are delays // | a2 | b2 | ">" represent multiplications // +---<-----|---->----+ // To test this routine, use a biquad with a pole pair at z = (0.7 +- 0.1j), // and a double zero at z = -1.0, which is a low-pass. The transfer function is: // 1 + 2z^-1 + z^-2 // H(z) = ---------------------- // 1 - 1.4z^-1 + 0.5z^-2 // a1 = 1.4 // a2 = -0.5 // b1 = 2 // b2 = 1 // This filter conforms to the biquad test in BDT, since it has coefficients // larger than 1.0 in magnitude, and b0=1. (Note that the a's have a negative // sign.) // This filter can be simulated in matlab. To simulate one biquad, use // A = [1.0, -1.4, 0.5] // B = [1, 2, 1] // Y=filter(B,A,X) // To simulate two cascaded biquads, use // Y=filter(B,A,filter(B,A,X)) // SCALED COEFFICIENTS: // -------------------- // In order to conform to 1.15 representation, must scale coeffs by 0.5. // This requires an additional internal re-scale. The equations for the Type II // filter are: // t1 = x + a1*t1*z^-1 + a2*t1*z^-2 // y = b0*t1 + b1*t1*z^-1 + b2*t1*z^-2 // (Note inclusion of term b0, which in the example is b0 = 1.) // If all coeffs are replaced by // ai --> ai' = 0.5*a1 // then the two equations become // t1 = x + 2*a1'*t1*z^-1 + 2*a2'*t1*z^-2 // 0.5*y = b0'*t1 + b1'*t1*z^-1 + b2'*t1*z^-2 // which can be implemented as: // 2.0 b0'=0.5 // x ---------+--->-----|---->----+-------y // | |t1 | // | D | // | a1' | b1' | // +---<-----|---->----+ // | | | // | D | // | a2' | b2' | // +---<-----|---->----+ // But, b0' can be eliminated by: // x ---------+---------|---------+-------y // | | | // | V 2.0 | // | | | // | |t1 | // | D | // | a1' | b1' | // +---<-----|---->----+ // | | | // | D | // | a2' | b2' | // +---<-----|---->----+ // Function biquadf() computes this implementation on float data. // CASCADED BIQUADS // ---------------- // Cascaded biquads are simulated by simply cascading copies of the // filter defined above. However, one must be careful with the resulting // filter, as it is not very stable numerically (double poles in the // vecinity of +1). It would of course be better to cascade different // filters, as that would result in more stable structures. // The functions biquadf() and biquadR() have been tested with up to 3 // stages using this technique, with inputs having small signal amplitude // (less than 0.001) and under 300 samples. // // In order to pipeline, need to maintain two pointers into the state // array: one to load (I0) and one to store (I2). This is required since // the load of iteration i+1 is hoisted above the store of iteration i. .include "testutils.inc" start // I3 points to input buffer loadsym I3, input; // P1 points to output buffer loadsym P1, output; R0 = 0; R7 = 0; P2 = 10; LSETUP ( L$0 , L$0end ) LC0 = P2; L$0: // I0 and I2 are pointers to state loadsym I0, state; I2 = I0; // pointer to coeffs loadsym I1, Coeff; R0.H = W [ I3 ++ ]; // load input value into RH0 A0.w = R0; // A0 holds x P2 = 2; LSETUP ( L$1 , L$1end ) LC1 = P2; // load 2 coeffs into R1 and R2 // load state into R3 R1 = [ I1 ++ ]; MNOP || R2 = [ I1 ++ ] || R3 = [ I0 ++ ]; L$1: // A1=b1*s0 A0=a1*s0+x A1 = R1.L * R3.L, A0 += R1.H * R3.L || R1 = [ I1 ++ ] || NOP; // A1+=b2*s1 A0+=a2*s1 // and move scaled value in A0 (t1) into RL4 A1 += R2.L * R3.H, R4.L = ( A0 += R2.H * R3.H ) (S2RND) || R2 = [ I1 ++ ] || NOP; // Advance state. before: // R4 = uuuu t1 // R3 = stat[1] stat[0] // after PACKLL: // R3 = stat[0] t1 R5 = PACK( R3.L , R4.L ) || R3 = [ I0 ++ ] || NOP; // collect output into A0, and move to RL0. // Keep output value in A0, since it is also // the accumulator used to store the input to // the next stage. Also, store updated state L$1end: R0.L = ( A0 += A1 ) || [ I2 ++ ] = R5 || NOP; // store output L$0end: W [ P1 ++ ] = R0; // Check results loadsym I2, output; R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x0028 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x0110 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x0373 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x075b ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x0c00 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x1064 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x13d3 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x15f2 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x16b9 ); R0.L = W [ I2 ++ ]; DBGA ( R0.L , 0x1650 ); pass .data state: .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .data Coeff: .dw 0x7fff .dw 0x5999 .dw 0x4000 .dw 0xe000 .dw 0x7fff .dw 0x5999 .dw 0x4000 .dw 0xe000 input: .dw 0x0028 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 output: .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000 .dw 0x0000