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27
28 #ifdef HAVE_CONFIG_H
29 #include "config.h"
30 #endif
31
32 /* conversion between prediction filter coefficients and LSFs */
33 /* order should be even */
34 /* a piecewise linear approximation maps LSF <-> cos(LSF) */
35 /* therefore the result is not accurate LSFs, but the two */
36 /* functions are accurate inverses of each other */
37
38 #include "SigProc_FIX.h"
39 #include "tables.h"
40
41 #define QA 16
42
43 /* helper function for NLSF2A(..) */
silk_NLSF2A_find_poly(opus_int32 * out,const opus_int32 * cLSF,opus_int dd)44 static OPUS_INLINE void silk_NLSF2A_find_poly(
45 opus_int32 *out, /* O intermediate polynomial, QA [dd+1] */
46 const opus_int32 *cLSF, /* I vector of interleaved 2*cos(LSFs), QA [d] */
47 opus_int dd /* I polynomial order (= 1/2 * filter order) */
48 )
49 {
50 opus_int k, n;
51 opus_int32 ftmp;
52
53 out[0] = silk_LSHIFT( 1, QA );
54 out[1] = -cLSF[0];
55 for( k = 1; k < dd; k++ ) {
56 ftmp = cLSF[2*k]; /* QA*/
57 out[k+1] = silk_LSHIFT( out[k-1], 1 ) - (opus_int32)silk_RSHIFT_ROUND64( silk_SMULL( ftmp, out[k] ), QA );
58 for( n = k; n > 1; n-- ) {
59 out[n] += out[n-2] - (opus_int32)silk_RSHIFT_ROUND64( silk_SMULL( ftmp, out[n-1] ), QA );
60 }
61 out[1] -= ftmp;
62 }
63 }
64
65 /* compute whitening filter coefficients from normalized line spectral frequencies */
silk_NLSF2A(opus_int16 * a_Q12,const opus_int16 * NLSF,const opus_int d)66 void silk_NLSF2A(
67 opus_int16 *a_Q12, /* O monic whitening filter coefficients in Q12, [ d ] */
68 const opus_int16 *NLSF, /* I normalized line spectral frequencies in Q15, [ d ] */
69 const opus_int d /* I filter order (should be even) */
70 )
71 {
72 /* This ordering was found to maximize quality. It improves numerical accuracy of
73 silk_NLSF2A_find_poly() compared to "standard" ordering. */
74 static const unsigned char ordering16[16] = {
75 0, 15, 8, 7, 4, 11, 12, 3, 2, 13, 10, 5, 6, 9, 14, 1
76 };
77 static const unsigned char ordering10[10] = {
78 0, 9, 6, 3, 4, 5, 8, 1, 2, 7
79 };
80 const unsigned char *ordering;
81 opus_int k, i, dd;
82 opus_int32 cos_LSF_QA[ SILK_MAX_ORDER_LPC ];
83 opus_int32 P[ SILK_MAX_ORDER_LPC / 2 + 1 ], Q[ SILK_MAX_ORDER_LPC / 2 + 1 ];
84 opus_int32 Ptmp, Qtmp, f_int, f_frac, cos_val, delta;
85 opus_int32 a32_QA1[ SILK_MAX_ORDER_LPC ];
86 opus_int32 maxabs, absval, idx=0, sc_Q16;
87
88 silk_assert( LSF_COS_TAB_SZ_FIX == 128 );
89 silk_assert( d==10||d==16 );
90
91 /* convert LSFs to 2*cos(LSF), using piecewise linear curve from table */
92 ordering = d == 16 ? ordering16 : ordering10;
93 for( k = 0; k < d; k++ ) {
94 silk_assert(NLSF[k] >= 0 );
95
96 /* f_int on a scale 0-127 (rounded down) */
97 f_int = silk_RSHIFT( NLSF[k], 15 - 7 );
98
99 /* f_frac, range: 0..255 */
100 f_frac = NLSF[k] - silk_LSHIFT( f_int, 15 - 7 );
101
102 silk_assert(f_int >= 0);
103 silk_assert(f_int < LSF_COS_TAB_SZ_FIX );
104
105 /* Read start and end value from table */
106 cos_val = silk_LSFCosTab_FIX_Q12[ f_int ]; /* Q12 */
107 delta = silk_LSFCosTab_FIX_Q12[ f_int + 1 ] - cos_val; /* Q12, with a range of 0..200 */
108
109 /* Linear interpolation */
110 cos_LSF_QA[ordering[k]] = silk_RSHIFT_ROUND( silk_LSHIFT( cos_val, 8 ) + silk_MUL( delta, f_frac ), 20 - QA ); /* QA */
111 }
112
113 dd = silk_RSHIFT( d, 1 );
114
115 /* generate even and odd polynomials using convolution */
116 silk_NLSF2A_find_poly( P, &cos_LSF_QA[ 0 ], dd );
117 silk_NLSF2A_find_poly( Q, &cos_LSF_QA[ 1 ], dd );
118
119 /* convert even and odd polynomials to opus_int32 Q12 filter coefs */
120 for( k = 0; k < dd; k++ ) {
121 Ptmp = P[ k+1 ] + P[ k ];
122 Qtmp = Q[ k+1 ] - Q[ k ];
123
124 /* the Ptmp and Qtmp values at this stage need to fit in int32 */
125 a32_QA1[ k ] = -Qtmp - Ptmp; /* QA+1 */
126 a32_QA1[ d-k-1 ] = Qtmp - Ptmp; /* QA+1 */
127 }
128
129 /* Limit the maximum absolute value of the prediction coefficients, so that they'll fit in int16 */
130 for( i = 0; i < 10; i++ ) {
131 /* Find maximum absolute value and its index */
132 maxabs = 0;
133 for( k = 0; k < d; k++ ) {
134 absval = silk_abs( a32_QA1[k] );
135 if( absval > maxabs ) {
136 maxabs = absval;
137 idx = k;
138 }
139 }
140 maxabs = silk_RSHIFT_ROUND( maxabs, QA + 1 - 12 ); /* QA+1 -> Q12 */
141
142 if( maxabs > silk_int16_MAX ) {
143 /* Reduce magnitude of prediction coefficients */
144 maxabs = silk_min( maxabs, 163838 ); /* ( silk_int32_MAX >> 14 ) + silk_int16_MAX = 163838 */
145 sc_Q16 = SILK_FIX_CONST( 0.999, 16 ) - silk_DIV32( silk_LSHIFT( maxabs - silk_int16_MAX, 14 ),
146 silk_RSHIFT32( silk_MUL( maxabs, idx + 1), 2 ) );
147 silk_bwexpander_32( a32_QA1, d, sc_Q16 );
148 } else {
149 break;
150 }
151 }
152
153 if( i == 10 ) {
154 /* Reached the last iteration, clip the coefficients */
155 for( k = 0; k < d; k++ ) {
156 a_Q12[ k ] = (opus_int16)silk_SAT16( silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ) ); /* QA+1 -> Q12 */
157 a32_QA1[ k ] = silk_LSHIFT( (opus_int32)a_Q12[ k ], QA + 1 - 12 );
158 }
159 } else {
160 for( k = 0; k < d; k++ ) {
161 a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */
162 }
163 }
164
165 for( i = 0; i < MAX_LPC_STABILIZE_ITERATIONS; i++ ) {
166 if( silk_LPC_inverse_pred_gain( a_Q12, d ) < SILK_FIX_CONST( 1.0 / MAX_PREDICTION_POWER_GAIN, 30 ) ) {
167 /* Prediction coefficients are (too close to) unstable; apply bandwidth expansion */
168 /* on the unscaled coefficients, convert to Q12 and measure again */
169 silk_bwexpander_32( a32_QA1, d, 65536 - silk_LSHIFT( 2, i ) );
170 for( k = 0; k < d; k++ ) {
171 a_Q12[ k ] = (opus_int16)silk_RSHIFT_ROUND( a32_QA1[ k ], QA + 1 - 12 ); /* QA+1 -> Q12 */
172 }
173 } else {
174 break;
175 }
176 }
177 }
178
179