SILK fixes following last codec WG meeting

decoder:
- fixed incorrect scaling of filter states for the smallest quantization
  step sizes
- NLSF2A now limits the prediction gain of LPC filters

encoder:
- increased damping of LTP coefficients in LTP analysis
- increased white noise fraction in noise shaping LPC analysis
- introduced maximum total prediction gain.  Used by Burg's method to
  exit early if prediction gain is exceeded.  This improves packet
  loss robustness and numerical robustness in Burg's method
- Prefiltered signal is now in int32 Q10 domain, from int16 Q0
- Increased max number of iterations in CBR gain control loop from 5 to 6
- Removed useless code from LTP scaling control
- Optimization: smarter LPC loop unrolling
- Switched default win32 compile mode to be floating-point

resampler:
- made resampler have constant delay of 0.75 ms; removed delay
  compensation from silk code.
- removed obsolete table entries (~850 Bytes)
- increased downsampling filter order from 16 to 18/24/36 (depending on
  frequency ratio)
- reoptimized filter coefficients

silk/float/SigProc_FLP.h

@@ -50,8 +50,7 @@ void silk_bwexpander_FLP(
 /* compute inverse of LPC prediction gain, and                          */
 /* test if LPC coefficients are stable (all poles within unit circle)   */
 /* this code is based on silk_FLP_a2k()                                 */
-opus_int silk_LPC_inverse_pred_gain_FLP(    /* O    returns 1 if unstable, otherwise 0                          */
-    silk_float          *invGain,           /* O    inverse prediction gain, energy domain                      */
+silk_float silk_LPC_inverse_pred_gain_FLP(  /* O    return inverse prediction gain, energy domain               */
     const silk_float    *A,                 /* I    prediction coefficients [order]                             */
     opus_int32          order               /* I    prediction order                                            */
 );
@@ -108,9 +107,9 @@ void silk_insertion_sort_decreasing_FLP(
 silk_float silk_burg_modified_FLP(          /* O    returns residual energy                                     */
     silk_float          A[],                /* O    prediction coefficients (length order)                      */
     const silk_float    x[],                /* I    input signal, length: nb_subfr*(D+L_sub)                    */
+    const silk_float    minInvGain,         /* I    minimum inverse prediction gain                             */
     const opus_int      subfr_length,       /* I    input signal subframe length (incl. D preceeding samples)   */
     const opus_int      nb_subfr,           /* I    number of subframes stacked in x                            */
-    const silk_float    WhiteNoiseFrac,     /* I    fraction added to zero-lag autocorrelation                  */
     const opus_int      D                   /* I    order                                                       */
 );